Tag: cybersecurity trends

Redefining Digital Security: Innovations in Cybersecurity Analytics

Posted on by Nicole Tidwell

In our digitally driven world, cybersecurity threats loom larger and more complex than ever before. Against this backdrop, cybersecurity analytics has emerged as a critical shield to outsmart sophisticated cyber threats. Central to this evolution is Sertainty and its UXP Technology, a trailblazer in Self-Protecting data security and a major catalyst to strategic partnerships that redefine the boundaries of cybersecurity analytics.

The Growing Need for Cybersecurity Analytics

Cyber threats have transformed in severity. Gone are the days when simple firewalls and antivirus software sufficed to safeguard a network. Today’s digital villains wield advanced tools that ranked cybercrime as a top ten most severe global risks by the World Economic Forum in 2023.

This new era demands a shift towards more sophisticated cybersecurity protocols, such as real-time data analysis and predictive capabilities, to stay ahead of malicious actors. Among these, cybersecurity analytics is perceived as the linchpin in understanding and neutralizing cyber threats. It transcends traditional defense mechanisms, enabling proactive threat detection, in-depth analysis, and timely response. 

A crucial aspect of cybersecurity analytics technologies is their contribution to defense-in-depth frameworks. This approach to cybersecurity involves multiple layers of defense spread across different parts of a network.

Today, it’s not enough to “set and forget” digital defenses or rely on a single, unchanging methodology. Integrating and continuously leveraging advanced analytics to evolve cybersecurity strategies has become a necessity for survival in today’s cyber terrain. 

Best Practices in Cybersecurity Analytics

The integration of technologies like AI opens the door for transformation in cybersecurity strategies. AI brings a data analyst capability regarding advanced data processing and pattern recognition, enabling security systems to identify and respond to threats more rapidly and accurately than ever before. By analyzing vast amounts of data at an unprecedented speed, AI can detect anomalies that might indicate a security breach, thereby enhancing the effectiveness of cybersecurity measures. 

Artificial intelligence and the Internet of Things (IoT) technologies enhance this layered defense strategy by adding advanced detection and response capabilities at various levels. AI’s ability to learn and adapt to new threats complements the defense-in-depth strategy by continuously evolving the security measures in place. This not only adds depth to the cybersecurity defenses but also ensures a more resilient and robust protection system.

Similarly, IoT technology expands the scope of cybersecurity analytics by extending protection to a myriad of interconnected devices. The vast network of IoT devices generates a large amount of data, which, when analyzed, can provide valuable insights into potential security threats. IoT devices, often being the weakest link in security, can benefit significantly from advanced analytics, ensuring that threats are identified and mitigated before they can exploit these devices. 

At the core of effective cybersecurity analytics is a data-centric approach. This strategy prioritizes the protection of data itself rather than just focusing on the perimeter defenses. By empowering data, for instance, with the Sertainty Active Intelligence, each piece of information becomes capable of autonomously defending itself against threats. This approach aligns perfectly with the principles of defense-in-depth, as it adds an additional, critical layer of security that focuses on protecting the data directly, no matter where it resides within the network. 

Common Cybersecurity Analytics Challenges

Mastering cybersecurity analytics is marked by a myriad of challenges. These challenges arise from various aspects of the cybersecurity domain and require a multifaceted approach for effective management and resolution.

One of the primary challenges in cybersecurity analytics is the constantly shifting nature of emerging cyber threats. Hackers and cybercriminals are continually developing new techniques and strategies to breach security systems. This means that the algorithms and models used in cybersecurity analytics must also be constantly updated and reimagined to identify and counteract new attacks. Staying ahead of these evolving threats requires not only advanced technology but also a deep understanding of the latest trends in cybercrime. 

Another potential area of concern is the fact that cybersecurity threats require immediate identification and response. The challenge here is not just detecting threats but doing so in real time and providing a rapid response. Delayed detection or response can lead to significant damage, making speed and efficiency critical components in cybersecurity analytics. 

With the expansion of digital networks and the proliferation of IoT devices, the volume of data that needs to be analyzed for potential threats has also grown exponentially. This massive volume of data presents a significant challenge, as it requires sophisticated tools and algorithms to process and analyze matters effectively. Moreover, the complexity of this data, which often includes unstructured and varied formats, adds another layer of difficulty in extracting meaningful insights for cybersecurity. 

In many organizations, cybersecurity systems need to integrate with various other systems and technologies. This integration can sometimes be challenging due to compatibility and interoperability issues. Ensuring that different systems can effectively communicate and work together is crucial for efficient cybersecurity analytics.

Similarly, the field of cybersecurity analytics is highly specialized, requiring a combination of skills in data science, cybersecurity, and information technology. There is often a skill gap in the industry, with a shortage of professionals who possess the comprehensive expertise needed to effectively analyze and interpret cybersecurity data. This shortage can hinder the development and implementation of effective cybersecurity analytics strategies. 

Despite these challenges, advancements in technology and strategic collaborations are creating pathways to overcome these hurdles. Innovative solutions are being developed to address the specific needs of cybersecurity analytics, including more sophisticated data analysis tools, improved integration capabilities, and real-time threat detection and response systems. These solutions, often born from collaborations between industry leaders and cybersecurity experts, are key to effectively navigating the challenges of cybersecurity analytics and enhancing overall digital security. 

Advancements in Cybersecurity Analytics

Looking to the future, the recent partnership between Sertainty and GuardDog AI marks a significant advancement in cybersecurity analytics. GuardDog AI’s prowess in AI-driven incident response, combined with Sertainty’s Data Security Platform, creates a formidable force in cybersecurity. This collaboration enhances cybersecurity analytics by streamlining incident responses and fortifying data protection strategies. 

AI’s role in cybersecurity incident response is pivotal. When combined with the expansive capabilities of IoT, it leads to a more comprehensive analytical framework. This integration not only bolsters security measures but also brings a nuanced understanding of cyber threats, enhancing overall analytics efficiency. 

These strategic collaborations aren’t just about enhancing current security measures; they’re about setting new industry standards. By redefining the paradigm of data security, Sertainty and its partners are charting a course toward a future where cybersecurity is more intelligent, responsive, and impenetrable. 

Meeting the Future of Cybersecurity with Sertainty

The advancement of cybersecurity analytics is a cornerstone in the modern digital landscape, and Sertainty, along with its strategic partners, is at the forefront of this revolution. By staying informed and adopting these advanced cybersecurity measures, organizations can ensure they are well-equipped to face the cyber challenges of today and tomorrow. 

As a leader in data-level security and self-protecting data technology, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself. These protocols mean that even if systems are compromised or accessed from the inside, all data stored in them remains secure. 

At Sertainty, we know that the ability to maintain secure files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered data solutions that are intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing self-protecting data solutions that adapt and grow to defend sensitive data. Security threats may be inevitable, but with Sertainty, privacy loss doesn’t have to be. 

EtherHiding: Understanding and Mitigating the New Cybersecurity Threat

Posted on by Nicole Tidwell

The world of technology is ever-advancing, opening new doors to interoperability and global connectivity. However, cybersecurity threats keep pace with each new evolution, becoming as consistent as the advancements themselves. One such emerging threat in the blockchain space, catching the attention of security experts worldwide, is EtherHiding. This new method of cyberattack poses unique challenges and necessitates a fresh approach to data protection. 

What Is EtherHiding?

EtherHiding is a sophisticated cybersecurity threat that utilizes blockchain technology to conceal malicious code. This technique represents a significant shift in the landscape of digital threats, merging the advanced capabilities of blockchain with the nefarious intentions of hackers.

At the heart of these attacks lies an ingenious exploitation of the Binance Smart Chain (BSC), a blockchain platform known for its efficiency and versatility in handling smart contracts. Cybercriminals often target WordPress sites, which are widely used due to their versatility and popularity. These sites become unwitting conduits in a sophisticated cyberattack chain. 

The attack begins with the defacement of these websites, often masked under the guise of legitimate-looking browser update prompts. Unsuspecting users, believing these prompts to be authentic, are tricked into downloading malware. This deceitful strategy represents a departure from conventional hacking methods that typically target system vulnerabilities directly. Instead, EtherHiding exploits the trust and routine behaviors of users, turning regular web interactions into potential security breaches.

Once the user interacts with these deceptive overlays, the attack leverages the Binance Smart Chain to embed malicious code within the blockchain transactions. This method effectively circumvents traditional cybersecurity measures, which are primarily designed to shield against direct intrusions into the system rather than insidious code embedded in an otherwise legitimate blockchain transaction. The seamless integration of the malicious code into the blockchain makes it a particularly resilient form of malware, benefiting from the blockchain’s decentralized and immutable nature.

As such, these techniques represent a confluence of cyberattack methodologies — combining social engineering to lure victims with the advanced use of blockchain technology to execute the attack. This novel approach necessitates a reevaluation of standard cybersecurity practices and highlights the need for more sophisticated, adaptive, and comprehensive digital security strategies. 

Impacts on Cybersecurity

The introduction of EtherHiding into the cybersecurity landscape marks a significant escalation in cyber threats, particularly given its use of blockchain technology. This innovative method has broad implications.

  • Increased Vulnerability of Sensitive Data: This type of attack targets not just financial systems but any blockchain-based platform, putting a wide range of sensitive data at risk. This could include personal identification information, trade secrets, and even national security data. The confidentiality and integrity of this data are compromised, leading to potential identity theft, financial fraud, and other forms of cybercrime. 
  • Erosion of Trust in Blockchain: Blockchain technology is lauded for its security and immutability. However, EtherHiding exploits these features to hide malicious code, thereby undermining trust in blockchain networks. This could slow down the adoption of blockchain technology in various sectors, including finance, healthcare, and government. 
  • Financial Implications: For businesses, the costs associated with breaches like these can be multifaceted. They range from direct financial losses due to theft or fraud to indirect costs such as damage control, system audits, increased insurance premiums, and loss of customer trust. 
  • Regulatory and Compliance Challenges: Companies that fall victim to attacks may face regulatory scrutiny and compliance issues, especially in industries where data protection is heavily regulated. This can result in hefty fines and legal costs, further exacerbating the financial impact. 

Challenges in Detecting and Mitigating EtherHiding

Detecting and mitigating EtherHiding poses significant challenges, predominantly due to its advanced nature and the incorporation of blockchain technology. Traditional cybersecurity measures, typically geared towards identifying code anomalies or unauthorized access, often fall short in the face of these attacks. This is because the malicious code is cleverly embedded within blockchain transactions, enabling it to evade detection and remain a hidden threat for prolonged periods. This stealthy characteristic allows the malicious code to inflict considerable damage before being discovered. 

Another critical challenge is the immutable nature of blockchain technology. Once EtherHiding embeds its malicious code into a blockchain, altering or removing it becomes an impossible task due to the blockchain’s inherent design. This characteristic of blockchain renders traditional mitigation strategies, which often involve removing or altering the code, ineffective. 

Furthermore, these attacks exhibit a dynamic and adaptive nature. Attackers can modify and update the embedded code, constantly changing the threat’s behavior and making it a moving target for cybersecurity teams. This necessitates continuous and vigilant monitoring and frequent updating of security protocols, which can be both complex and resource-intensive. 

Responding to Incidents

The process of responding to an EtherHiding attack is multifaceted, extending beyond mere technical resolution. It involves navigating legal, regulatory, and reputational aspects, adding layers of complexity to the response strategy. Organizations must balance these considerations while striving to secure their systems against such attacks.

Effectively combatting sophisticated breaches of this nature demands specialized knowledge in both cybersecurity and blockchain technology. This specialized knowledge is not always readily available, presenting an additional hurdle for many organizations in their efforts to secure their systems against this sophisticated cyber threat. The convergence of these factors makes EtherHiding a particularly formidable challenge in the field of cybersecurity.

Best Practices to Protect Against EtherHiding

To guard against this new style of cyber threat, organizations must adopt a multi-layered security strategy. This includes staying vigilant, regularly updating security protocols, and educating employees about the risks of such sophisticated attacks. Implementing comprehensive cybersecurity is key to protecting sensitive data. Furthermore, the dynamic nature of threats like EtherHiding calls for adaptive cybersecurity measures that can evolve to overcome groundbreaking attack vectors.

Comprehensive Data Security Solutions 

In response to the evolving digital landscape, Sertainty technology offers a robust cybersecurity solution. Our data-level security approach is uniquely equipped to combat the new, sophisticated generation of threats. By empowering data to protect itself, Sertainty provides a resilient line of defense against advanced cyberattacks — no matter where, when, or how they occur.

Understanding and addressing emerging cyber threats is crucial in today’s digital age, and staying proactive can make a significant difference in safeguarding against such advanced attacks. For those looking to fortify their cybersecurity defenses against innovative threats like EtherHiding, exploring Sertainty’s solutions is a step toward achieving advanced cybersecurity protection.

Why Cybersecurity Is the Cornerstone of Data as a Product (DaaP)

Posted on by Nicole Tidwell

In today’s rapidly evolving digital landscape, the importance of data security cannot be overstated. We’re entering an era where data is not just a byproduct of business operations; it’s the lifeblood of success. This brings us to the concept of Data as a Product (DaaP), a strategic approach that’s reshaping how organizations perceive and leverage their data. In this journey, we’ll explore the profound role of data-level security in DaaP and how it can be the key to unlocking unprecedented advantages in the data-driven world.

Understanding Data as a Product

Data as a Product isn’t just a buzzword; it’s a transformative strategy for the way we handle and consider information. At its core, DaaP involves treating your data not merely as a supporting actor but as the star of the show. It means packaging, presenting, and delivering your data as if it were a product on the market. 

The motivation behind this shift is clear: Data, when managed and secured correctly, has the potential to generate immense value. More organizations are adopting DaaP to monetize their data assets, enable data-driven decision-making, and gain a competitive edge in their industries. 

Viewing data as a product is gaining traction not only in the private sector but also among federal agencies. Increasingly, federal agencies are recognizing the power of DaaP to harness the data they generate and curate, enabling them to make data-driven decisions, unlock new insights, and enhance their overall effectiveness. 

These benefits for both federal organizations and private companies are undeniable, but they come with a caveat: the need for impeccable data security.

The Role of Data-Level Security in DaaP

Data-level security is the linchpin of a robust and effective DaaP strategy. While traditional security models have primarily relied on perimeter defenses like firewalls and encryption, they often fall short when it comes to safeguarding the core asset: the data itself. Imagine a castle with well-guarded gates but no protection for the treasures inside — this analogy mirrors the limitations of perimeter-focused approaches.

Data-level security takes a revolutionary approach by redefining the perimeter. Instead of concentrating solely on external threats, it recognizes that data can traverse beyond the traditional boundaries of an enterprise’s control. This means that your data can be anywhere — within your corporate network, stored in the cloud, or in transit to a partner site — and still remain shielded. By embedding security directly into the data, it becomes an active participant in its own defense, ensuring uninterrupted protection.

Eliminating Data Silos

Data silos have long been a headache for organizations, creating fragmented and disconnected repositories of information, each with its own set of security protocols. When considering Data as a Product, data must seamlessly flow across departments and partners, meaning these silos pose a significant challenge. However, data-level security brings much-needed order to this chaos.

By unifying and standardizing security across all data, regardless of its location or type, data-level security eliminates the inherent vulnerabilities of data silos. Whether you’re dealing with customer data in your CRM, financial records in your accounting software, or critical research information in cloud storage, this approach ensures a consistent and high level of secure data governance. It not only streamlines data management but also enhances security in a DaaP ecosystem where trust and reliability are paramount.

Simplified and Enhanced Security

Traditional security measures can often resemble an intricate maze constructed around your data — challenging to navigate, maintain, and secure. Data-level security flips this paradigm entirely. When your data is inherently safeguarded, it obviates the need for complex layers of defense.

In practice, this translates to streamlined security policies, reduced complexity, and substantial cost savings. Moreover, data-level protection provides unparalleled security by ensuring that only authorized individuals and systems can access and interact with your data. This level of security is especially critical in DaaP, where data is not only a product but also a trusted currency. With data-level security, consumer trust is bolstered and the integrity of data is maintained throughout its journey, whether it’s at rest or in transit.

Best Practices for Data-Level Security in DaaP

Efficiently implementing data-level security necessitates a methodical approach deeply rooted in cybersecurity principles. Commence with a thorough data audit, meticulously identifying and categorizing sensitive data. Subsequently, formulate explicit policies and access controls that harmonize with your DaaP objectives. 

It’s imperative that the data security solution you opt for is robust and can seamlessly integrate within your existing infrastructure. Vigilantly conduct periodic audits and surveillance of data access, promptly addressing any detected anomalies with an eye toward emerging threat vectors. 

Last but not least, enlighten your teams on the paramount significance of data-level security and cultivate a corporate ethos where data protection is intrinsic. These strategies will act as your guiding light on the path to a secure and prosperous DaaP strategy.

Embracing the Future of Secure Data Governance

The digital landscape is evolving, and data is at the center of it all. That’s why the road to success in the data-driven world of DaaP is paved with data-level security. It’s the foundation that eliminates data silos, simplifies security practices, and ensures that your data remains a trusted and valuable asset. 

As you embark on your DaaP journey, remember that the security of your data is non-negotiable. Implementing the right secure data governance strategy will not only protect your data but empower you to unlock the full potential of Data as a Product. 

As a leader in data-level security and self-protecting data technology, Sertainty knows that maintaining secure access to your files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered data solutions that are intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing self-protecting data solutions that adapt and grow to defend sensitive data. New threats to your data may be inevitable, but with Sertainty, privacy loss doesn’t have to be. 

DevSecOps: The Future of Built-In Cybersecurity

Posted on by Nicole Tidwell

In today’s volatile world of ever-emerging cybersecurity threats, effective security solutions are more essential than ever before. In the past, cybersecurity was perceived as ancillary to Information Technology activities, but developers are increasingly turning to new methods that blend such more effectively like DevSecOps—which is a process and not technology. It’s a cultural and engineering practice that breaks down barriers and opens collaboration between software development, security, and operations to instill a rationale oriented around automation and delivery. 

What Is DevSecOps?

In the domain of cybersecurity and software development, modern challenges are being met by a strategic approach known as DevSecOps. In essence, it’s a cohabitation encompassing Security and Operations development. DevSecOps embodies a philosophy that seeks to integrate security practices seamlessly into the software development lifecycle. 

DevSecOps promotes a cultural shift that shatters traditional silos, fostering a shared responsibility for security across the development pipeline. This means that security isn’t merely an add-on or a final checkpoint. It becomes a proactive and integral part of every phase: planning, coding, testing, and deployment. Vulnerabilities and risks are identified early, allowing for timely mitigation and reducing the potential impact of security breaches.

While it may seem simple to code security into your programs, not all factors are necessarily in a user’s control. Today, many companies employ in-house software engineers, albeit, much of the code is programmed by open-source developers. In fact, a 2019 report found that 96% of codebases contain at least some open-source code. While using open-source code does not negate the possibility of DevSecOps, it does mean that security solutions must account for all code, including programming written by other developers. 

DevSecOps, in its essence, promotes harmony, collaboration, and a shared sense of responsibility among development, security, and operations. It envisions a world where security isn’t an obstacle but a guiding principle, enabling organizations to build resilient, secure, and high-quality software while maintaining agility and speed. In this paradigm, security is no longer a checkpoint — it’s the guiding star that illuminates the path to digital resilience.

The Current State of DevSecOps

According to the 2023 Application Development Software Global Market Report, the application development software market is expected to grow from $334.86 billion this year to $915.96 billion in 2027. Not only are those numbers significant, but they represent an average Combined Annual Growth Rate (CAGR) of well over 28%. 

Enterprises and IT Integrators are continuously looking to stage projects along five phases: business modeling, data modeling, process modeling, application generation, and testing and turnover. Applying cryptography from the start has been difficult due to a dependency on a key management system that encrypts and decrypts an application or data and generates latency in the process.  

The Growing Importance of Inherent Security

Perhaps the greatest value of DevSecOps lies in its commitment to continuous improvement and learning. Teams that analyze security incidents and feedback are able to evolve their practices to stay ahead of emerging threats. This iterative loop empowers organizations to adapt quickly, enhancing their security posture in a landscape where cyber threats evolve at a rapid pace. 

As the digital landscape continues to evolve, the significance of DevSecOps has taken center stage, marking a pivotal turning point in the world of cybersecurity and software development. This is especially true in today’s landscape of emerging AI-enabled threat vectors. 

In the past year—2023—organizations have found themselves navigating an increasingly complex and perilous cybersecurity terrain, where the threats have become more diverse, dire, and persistent. It is in this dynamic environment that the DevSecOps approach emerged as twin pillars of resilience and adaptability. 

Regulations and Compliance

Gone are the days when security could be an afterthought—a mere hoop to jump through at the end of the development cycle. During 2023, the stakes and exposure to cyberattacks rose exponentially in which breaches Breaches led to severe financial losses, regulatory penalties, and the erosion of customer trust, thereby blurring a  traditional divide between development, security, and operations and making it no longer tenable or viable to work in a siloed mode. 

Henceforth, organizations are embracing digital transformation and cloud environments, microservices, and IoT devices, all of which introduce new attack vectors. The sheer diversity and complexity of these technologies demand a proactive security approach. DevSecOps advocates for the integration of security from the earliest stages, ensuring that vulnerabilities are identified and addressed before they can be exploited.

Failure to sufficiently protect data can subject companies to regulatory hot water. For instance, in the United States, all information related to individual health is protected under the Health Insurance Portability and Accountability Act of 1996 (HIPAA). Compliance with HIPAA regulations is dictated by the US Department of Health and Human Services and enforced by the Office for Civil Rights. Non-compliance with privacy laws such as HIPAA, CCPA legislation in California, or the GDPR (pertaining to EU subjects) is prone to penalization. 

In short, effective and dynamic security is necessary to stay on the right side of data protection laws. The DevSecOps approach becomes a catalyst for such agility. It empowers teams to respond swiftly to emerging threats, adapting their strategies in real-time. The iterative nature of DevSecOps ensures that security remains an evolving practice, aligned with the ever-changing threat landscape. 

The Future of DevSecOps

As we navigate the uncharted waters of 2023 and beyond, DevSecOps stands as a cornerstone of resilience, enabling organizations to not only weather the storms of cyber threats but also emerge stronger, more secure, and more adaptable than ever before. But how can businesses and agencies adopt a DevSecOps approach?

Enter self-protecting data solutions, such as Sertainty’s cutting-edge technology. By embedding intelligence directly into data files, self-protecting data can recognize and counter malicious activities, even in the absence of known vulnerabilities or patches. As a pioneer of this approach, Sertainty redefines how information is protected to ensure data privacy where perimeters fail. Using cutting-edge protocols and embedding intelligence directly into sensitive data files or datasets, Sertainty leverages patented processes to govern, track, and defend data through the files themselves. 

Instead of database security based on privileges to access the network directory where the file currently resides, Sertainty Self-Protecting Data technology empowers the files to defend themselves against malicious activity immediately. Sertainty UXP Technology recognizes itself through a Zero-Trust framework that contextualizes the environment, behavior, and action of the intended receiver — whether human, machine, or application. With these protocols, the data remains secure even in situations where systems have been compromised. 

Government agencies are recognizing the importance of this approach. In fact, an executive order from last year demands that all US federal agencies adopt a Zero-Trust security model to improve data security efforts. The Cybersecurity and Infrastructure Security Agency (CISA) has also been applying pressure on both the private and public sectors to increase commitment to digital security and Secure-by-Design Technology. 

Empower Your Built-In Security with Sertainty

Sertainty Technology automatically bakes in security at every phase of the software development lifecycle, enabling the development of secure software in a Waterfall or Agile construct. This enables the secure automation of processes, standardizations, protections, and contextualization of data. Moreover, Sertainty UXP Technology demonstrates homomorphic capabilities, specifying what needs to be decrypted and worked on. This is a huge operational gain, streamlining processes and touchpoints.

Through its UXP Technology, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself — whether in flight, in a developer’s sandbox, or in storage. These UXP Technology protocols mean that even if systems are compromised by AI tools or accessed from the inside, all data stored in them remains secure. 

At Sertainty, we know that maintaining secure files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing self-protecting data solutions that evolve and grow to defend sensitive data. With the proliferation of human and AI threats, security breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be. 

The Future of Data Security: AI, Self-Protecting Files, and Zero-Trust

Posted on by Nicole Tidwell

In today’s digital landscape, the future of data security is at the forefront of every organization’s concerns. With the constant evolution of cyber threats and the increasing complexity of our interconnected world, traditional security measures are no longer enough to safeguard sensitive information. 

Today, we’ll delve into the changing nature of information security threats, the limitations of conventional cybersecurity methods, and how innovative solutions like self-protecting files and zero-trust network access are shaping the future of data security. Join us on this journey as we explore the path to a more secure digital future, where organizations can protect their data with confidence.

The Evolution of Data Security

From the earliest days of computer networks, information security primarily focused on building robust perimeter defenses. Firewalls, intrusion detection systems, and access control were the standard tools in the cybersecurity arsenal. However, as technology advanced, so did the strategies of cybercriminals. The rise of sophisticated cyber threats has exposed the inadequacies of traditional security models. 

Limitations of Traditional Security Measures

The limitations of traditional security measures are evident in their inability to adapt to the evolving threat landscape. These methods often rely on static rules and predefined patterns to detect anomalies, making it challenging to detect novel attack vectors. Organizations find themselves in a constant game of catch-up, struggling to defend against new, innovative cyber threats.

Most traditional cybersecurity methods lean heavily on perimeter-based security. While firewalls and intrusion detection systems create a barrier between an organization’s internal network and the outside world, this approach has its limitations. Cybercriminals often exploit vulnerabilities to infiltrate this perimeter, making perimeter-based defenses an incomplete solution. Legacy systems and password-based authentication methods have become especially easy targets for attackers, as outdated software and weak passwords can provide cybercriminals with an open door to an organization’s sensitive data.

Insider threats pose another significant challenge. Malicious or negligent employees can bypass perimeter defenses, leading to data breaches from within.

Zero-Trust: Redefining Network Security

Zero-trust network access is a fundamental shift in the way we approach network security. Unlike traditional models that trust users and devices within the network, a zero-trust approach demands rigorous proof of legitimacy.

Zero-trust emphasizes the continuous verification and authentication of all users and devices, regardless of their location. This approach ensures that trust is never assumed, and access is granted based on real-time data and context. As a result, organizations can effectively protect their networks from both external threats and insider risks.

The Evolving Regulatory Landscape

Recognizing the need for a paradigm shift in cybersecurity, the United States government has taken significant steps to enhance data security. The Cybersecurity and Infrastructure Security Agency (CISA) has introduced the “Zero-Trust Maturity Model,” a framework designed to help organizations transition to zero-trust security. This model emphasizes continuous verification and authentication, ensuring that trust is never assumed, even within the network perimeter.

Executive Order 14028, titled “Improving the Nation’s Cybersecurity,” reinforces the government’s commitment to strengthening national cybersecurity defenses. The order highlights the importance of modernizing cybersecurity defenses and underscores the significance of implementing zero-trust principles. By aligning with government initiatives, organizations can stay ahead of cyber threats and contribute to a more secure digital landscape.

The Future of Data Security

Amid the evolving threat landscape, a revolutionary concept has emerged — self-protecting files. These files are not your typical data containers. Instead, they are intelligent, dynamic entities that possess the ability to protect themselves and the data they hold. 

Self-protecting files utilize cutting-edge technology to embed security directly into the data itself. They can determine who is accessing the data, where, when, and under what circumstances. If any aspect of the access does not align with pre-defined policies, the file can instantly revoke access or take other protective actions. 

Self-Protecting Data vs. Traditional Security

The advantages of self-protecting files over traditional security methods are profound. With self-protecting files, data protection becomes intrinsic, eliminating the need for perimeter defenses to protect data at rest. They also offer enhanced privacy and control, as data owners can define precisely how their data is accessed and used. This level of granularity in data security is a game-changer for organizations across various industries.

Other Emerging Security Technologies

Another type of emerging technology leverages advanced AI-driven algorithms to proactively identify and neutralize potential threats. They excel at detecting vulnerabilities that often evade traditional security measures, making them a vital component in safeguarding sensitive data.

One common focus of these technologies is securing the “edge territory” of networks, an often-ignored critical area where cyber criminals can exploit weaknesses. By concentrating on fortifying this network segment, these emerging solutions provide an additional layer of defense that is instrumental in today’s complex digital ecosystem.

Furthermore, these technologies are increasingly integrating with other cutting-edge security solutions, such as Sertainty’s technology and its Digital IDs. This integration not only enhances their capabilities but also fosters collaboration in creating dynamic ecosystems where data is both protected and empowered.

These pioneering approaches are setting a new industry standard for data security, coupled with a data-centric orientation. In a world where data security is paramount, these collaborations exemplify the potential of combining AI-driven security technologies to provide comprehensive protection in the digital age.

While these may seem fundamentally different than zero-trust, Sertainty technology can play an integral role in these platforms as well. For example, GuardDog AI‘s AI-powered Protective Cloud Services (PCS) platform employs cutting-edge technology to constantly scan and analyze network traffic in concert with the Sertainty software developer toolkit. 

This integration brings a unique fusion of technologies. Sertainty, a global data security leader, is known for its Data Privacy Platform, which empowers data files to protect themselves using a zero-trust methodology. This approach prioritizes data-centric security, ensuring privacy and integrity even in situations where traditional security measures may fall short.

Truly Secure Data with Sertainty

The future of data security lies in innovative solutions like self-protecting files and zero-trust network access. With the changing nature of cybersecurity threats and the limitations of traditional security measures, organizations must adapt to stay secure. 

Sertainty technology bridges the gap between technologies shaping the future of data security (self-protecting files and zero-trust network access) with a software development kit that can be seamlessly integrated into a wide range of applications. As we navigate the digital future, the path to a more secure data environment becomes clear — a path paved with innovation, adaptability, and trust in the face of evolving threats. 

Explore Sertainty’s solutions and embark on this journey towards a safer digital world.

Emerging Data Security Threats to Watch in 2024

Posted on by Nicole Tidwell

In today’s digital world, data is the lifeblood of organizations. It fuels decision-making, drives innovation, and is at the heart of every successful operation. However, as we march forward into 2024, the landscape of data security is more challenging and dynamic than ever before. New data security threats, both technological and human-driven, are on the horizon, demanding heightened vigilance and innovative solutions. 

The ability to proactively recognize and mitigate these threats is key to both protecting your most vital assets and maintaining regulatory compliance. In this article, we’ll examine some of the most prominent emerging data security threats to watch in 2024 as well as how organizations can comprehensively address them. 

Top Emerging Data Security Threats in 2024

AI-Powered Cyberattacks: The Rise of Adversarial AI

Artificial intelligence (AI) is a double-edged sword. While it powers many of our conveniences, it can also be harnessed for malicious purposes. In practical terms, AI technology has given rise to two distinct data security threats.

Firstly, generative AI’s ability to create convincing, human-like personas has made social engineering threats increasingly difficult to detect. The newfound accessibility of sophisticated machine learning tools also makes it easier for hackers to set an AI program to break through firewalls by trying endless combinations of possible credentials in “brute force” style attacks. 

This is not to say that AI is all bad news for cybersecurity. New tools, such as the innovative Protective Cloud Services (PCS) platform from GuardDog AI, can scan and analyze network traffic, proactively automating incident response steps to save precious time when responding to perimeter breaches. 

The Ransomware Evolution: Double Extortion and Beyond

Ransomware is evolving, and it’s not just about encrypting your data anymore. Ransomware capabilities and tactics have undergone a significant transformation in recent times, extending beyond the conventional act of encrypting data and posing even more potent threats to organizations. 

One notable evolution in this malicious strategy is the adoption of “double extortion” tactics. Instead of merely locking data away, cybercriminals are now leveraging the stolen data as an additional weapon in their arsenal. This entails a two-pronged approach. Alongside encrypting the victim’s data, attackers also threaten to publicly expose sensitive information unless a ransom is paid. This strategic shift underscores a fundamental realization made by cybercriminals — that data is not just valuable to the targeted organizations, but can be equally valuable to the attackers themselves. 

Supply Chain Vulnerabilities: Data Risks Beyond Your Control

The global digital supply chain is intricate, and data flows through it like a circulatory system. But it’s also a point of vulnerability. Attacks on this supply chain can have catastrophic repercussions, extending far beyond the organization directly targeted. 

The interconnected nature of supply chains means that a breach in one part of the network can potentially impact the data and operations of countless partners, creating a domino effect of data risks. As supply chains become increasingly global and digitally driven, safeguarding sensitive data throughout this intricate web has become crucial.

IoT and IIoT Devices: A Growing Attack Surface

The Internet of Things (IoT) is expanding exponentially, but so are its security risks. This is true in both private applications and the Industrial Internet of Things (IIoT). These devices collect and transmit data, which, while extremely useful, also widens the network edge, increasing the number of potential entry points into your system. 

Improperly secured IoT and IIoT devices can quickly transform from convenient tools to potential entry points for cybercriminals seeking to exploit vulnerabilities. These devices frequently lack robust security measures, leaving them susceptible to a variety of threats. Whether it’s a smart thermostat in a home or a sensor controlling a vital manufacturing process in an industrial setting, the security of these devices is paramount. 

Quantum Computing: A New Frontier for Cyber Threats

Quantum computing, once a realm of science fiction, is now becoming a reality. As we inch closer to practical quantum applications, the implications for data security are profound. Current encryption methods, which rely on the computational difficulty of factoring large numbers, may crumble in the face of quantum algorithms. 

Data security has traditionally provided a layered defense against intrusions. This is largely predicated on the assumption that a sufficiently layered defense-in-depth framework can counter intrusions. However, these defenses are built on computational limitations that quantum computers are poised to obliterate. Once useable quantum computing capability reaches the hands of malicious actors, the standard security algorithms that guard much of our most sensitive data today could be effortlessly decrypted. 

Insider Threats: The Danger Within

Insider threats, whether due to malice or negligence, are a persistent concern. These dangers even emanate from people you trust — your employees, contractors, or business partners. The issue with insider threats is that they’re not easy to spot because they’re coming from within your trusted circle.

Whether it’s someone intentionally leaking sensitive data to competitors or a well-meaning employee accidentally clicking on a malicious link, the result can be disastrous. When addressing insider threats, it’s not about securing your network’s external perimeter; it’s about safeguarding your internal secrets from those you trust the most.

The New Foundation of Data Resilience

As we move into 2024, the evolving data security landscape is both promising and perilous. New technologies bring unprecedented opportunities, but they also open doors to novel threats. In this era of data-driven decision-making, one thing is clear: improving data security to match these emerging threat vectors is not a luxury, but a necessity.

In the face of these powerful new data security threats, incremental improvements to existing network perimeters are insufficient. Instead, leaders are looking toward a new paradigm of data security. 

To address these and other mounting data security threats, leaders have begun to approach data as not just something to be safeguarded by perimeters, but as a vigilant protector in its own right. This means that data takes on an active role in looking after itself. So, whether your data is sitting safely within your company’s computer systems, floating up in the cloud, or traveling to another business, it’s always watching out for threats. 

By integrating data-level security into your cyber defense strategy, you create a resilient fortress around your most valuable asset — your data. In the face of quantum computing, AI-powered attacks, evolving ransomware, complex supply chains, IoT vulnerabilities, insider threats, and regulatory mazes, data-level security remains your constant and reliable guardian. Instead of relying on outer defenses, you have an inner champion that keeps your data safe no matter where it is.

In the words of Sertainty CSO Amir Sternhell, “The Sertainty UXP Technology is setting the standards in the IIoT world by protecting and maintaining the integrity of a sensor command to overcome the acceleration in phishing, fakes, and sabotage, attributed to adversarial AI. Rest assured that this upcoming year will witness a glut of holistic Data-Chain-of-Provenance and Digital Twin implementations — premised on the Sertainty Zero-Trust design principles — to quell intrusions into our Industrial Control Systems (ICS) and ransomware attacks.” 

Staying Ahead of Data Security Threats with Sertainty

As a leader in data-level security and self-protecting data technology, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself. These protocols mean that even if systems are compromised or accessed from the inside, all data stored in them remains secure. 

At Sertainty, we know that the ability to maintain secure files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered data solutions that are intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing self-protecting data solutions that adapt and grow to defend sensitive data. Security threats may be inevitable, but with Sertainty, privacy loss doesn’t have to be. 

Data Chain Custody Part 2: AI Data Security History, Flaws, and Emerging Solutions

Posted on by Nicole Tidwell

Recently, we discussed emerging open-source AI threat vectors, including the proliferation of potential open-source threats to private servers and data chains. Today, we’ll take a closer look at the history of AI data governance and discuss whether emerging trends in the marketplace can address them. 

When it comes to data security, AI presents a whole new field of dangers. But despite the high-tech nature of the data protection industry, even leading companies and government agencies are burying their heads in the sand and relying on existing security protocols to manage these threats. Regardless of whether or not your organization is on board with AI, these tools are here to stay. Reports have predicted that the AI market will experience a shocking Combined Annual Growth Rate (CAGR) of between 20.1% and 32.9%. As such, data privacy methodologies must pivot to take these AI tools into account.

AI Data Gathering and Security 2013–2023

While the underlying principles of artificial intelligence have existed for a long time, the widespread emergence of usable AI tech is less than a decade old. Depending on your definition, you may consider early algorithms introduced in the 1990s to be a precursor to current machine learning tools, but many experts generally regard 2013 as the origin of usable “deep learning,” as we now know it. 

The primary revolution at this stage was the use of five convolutional layers and three fully-connected linear layers and parallel graphics processing units (GPUs), as well as the introduction of a more efficient rectified linear unit for activation functions. 

The following year, in June 2014, the field of deep learning witnessed another serious advance with the introduction of generative adversarial networks (GANs), a type of neural network capable of generating new data samples similar to a training set. Essentially, two networks are trained simultaneously: (1) a generator network generates fake, or synthetic, samples, and (2) a discriminator network evaluates their authenticity.

2017 saw the introduction of transformer architecture that leverages the concept of self-attention to process sequential input data. This allowed for more efficient processing of long-range dependencies, which had previously been a challenge for traditional RNN architectures. 

Unlike traditional models, which would process words in a fixed order, transformers actually examine all the words at once. They assign something called attention scores to each word based on its relevance to other words in the sentence.

Generative Pretrained Transformer, or GPT-1, was introduced by OpenAI in June 2018. Since then, the program has gone through numerous evolutions. While OpenAI has not disclosed the specifics, it is assumed that the current iteration, GPT-4, has trillions of parameters. 

Emerging Trends in AI Data Security

On the other side of the same coin, some data security companies have already introduced tools utilizing the same AI protocols. These programs utilize the information-gathering and analytical capabilities of machine learning to identify potential threats and suggest courses of action to mitigate them. 

However, it’s important to note that — despite the use of new, powerful machine learning technology — the fundamental premise of this solution is based on a conventional understanding of data security. The system’s proactivity only extends as far as any traditional perimeter security and threat analysis (albeit in a more efficient manner). 

This inherent inadequacy means that even the most sophisticated form of conventionally-minded AI security can (theoretically) be exploited or circumvented by the same means as their predecessors.  

As such, truly addressing all potential threat vectors requires a complete rethink of how secure data governance is handled, rather than applying new technology to existing systems. 

AI-Informed Secure Data Governance 

Though many “leading” commercial tools rely on outdated security structures, a better solution is already available. Unlike traditional data privacy, Zero Trust security provides a proactive method for mitigating attacks. 

The key differentiator between Zero Trust and other, more traditional solutions is letting go of the (incorrect) assumption that sensitive databases can be secured simply by keeping malicious actors out. Rather than rely on a series of firewalls and trust that those with access are legitimately allowed to be there, Zero Trust security gives data the ability to protect itself. 

Following this methodology, Sertainty has redefined how information is protected to ensure data privacy even where firewalls fail. Using cutting-edge protocols and embedding intelligence directly into datasets, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself. These protocols mean that even if systems are compromised, data remains secure. 

With specific regard to emerging AI threats, the core Sertainty UXP Technology empowers data chain custodians to opt in or out of the use of Personal Identifying Information (PII) by AIs like ChatGPT. This ensures that organizations exposed to ChatGPT — as well as their employees and clients — maintain privacy, regulatory compliance, and protection in all scenarios. 

Sertainty UXP Technology also allows developers working with open-source AI programs like those from OpenAI to maintain their own privacy commitments by giving data files the ability to protect themselves and generating repositories of those who approve the processing or those who wish to opt out of data sharing.

Even regulators have taken notice of the shortcomings inherent in today’s cybersecurity paradigm and expressed interest in this new way of approaching data privacy. Prompted by both real and potential dangers, including AI threat vectors, an Executive Order titled “Improving The Nation’s Cybersecurity” has outlined the need for US federal agencies to move toward a zero-trust security model. 

Sertainty Data Privacy 

In the current landscape of trendy tech and buzzwords, concrete solutions are more vital than ever. Sertainty Zero Trust technology enables secure data governance and the training of AI models with a tried-and-true multi-layer security solution.

Sertainty leverages proprietary processes through its UXP Technology that enable data to govern, track, and defend itself — whether in flight, in a developer’s sandbox, or in storage. These UXP Technology protocols mean that even if systems are compromised by AI tools or accessed from the inside, all data stored in them remains secure. 

At Sertainty, we know that the ability to maintain secure files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs.

Secure-by-Design Technology

Posted on by Nicole Tidwell

While the need for total digital security has only increased over the past decades, the technology we rely on every day is often far from as secure as consumers assume. While virtually all devices, networks, and users utilize some form of information security practices, the overwhelming majority of these are separate systems that aim to keep outsiders from accessing vulnerable networks and data stores rather than improvements to the intrinsic security of the technology. 

While this may seem sufficient for some cases, the reality is that most security solutions are woefully inadequate when it comes to addressing the inherent flaws and vulnerabilities of cybersecurity technology. 

This issue has not escaped the notice of major regulatory agencies either. Earlier this year, Jen Easterly, director of the US Cybersecurity and Infrastructure Security Agency (CISA), criticized tech companies for their failure to prioritize the safety and privacy of consumers. This indictment is particularly potent coming from Easterly, who heads the United States’ national effort to understand, manage, and reduce risk to digital and physical infrastructure. 

The Burden of Safety

In many critical industries, a combination of legislation and presumed ethical responsibility mandate designers and manufacturers to account for the safe, secure usage of all new products from the outset. The world of technology, however, lacks many of these safeguards. 

The reasons for this are manifold. For one, the tech industry, as we currently know it, is still relatively young. For example, it was more than 80 years from the time automobiles were introduced until the US federal government mandated that all new cars being sold must have built-in seatbelts. 

Another reason that new technology pertaining to the cybersecurity space often lacks the oversight present in other industries relates to the nature of the threats in question. While the potential for accidental user-caused data breaches certainly exists to some extent, the majority of modern data threats come from malicious actors. This is the current industry dynamics that make it easier for tech companies to pass off the burden of safety, making it the responsibility of customers to protect themselves from attackers. 

While it is still up for debate on whether or not tech companies should be held responsible for the safety of their products, CISA Director Easterly was clear in her Carnegie Mellon University talk on where her organization stands regarding where the burden of security lies. 

“We find ourselves blaming the user for unsafe technology. In place of building-in effective security from the start, technology manufacturers are using us, the users, as their crash test dummies — and we’re feeling the effects of those crashes every day with real-world consequences,” she said. “This situation is not sustainable. We need a new model.” 

Information Security Legislation

Despite the lack of regulation surrounding the creation and distribution of software and Data-Centric technologies, the information stored and transferred using these tools is often bound by strict legislation. For instance, in the United States, all information related to individual health is protected under the Health Insurance Portability and Accountability Act of 1996 (HIPAA). Compliance with HIPAA regulations is dictated by the US Department of Health and Human Services and enforced by the Office for Civil Rights. 

Moreover, it should also be noted that non-compliance with privacy laws such as HIPAA for health-related data, CCPA legislation in California, or the GDPR (pertaining to EU subjects) is prone to penalization. 

Secure-by-Design Technology

Critical security concerns surrounding data that relies on digital privacy measures highlight the need for a better data protection paradigm than most individuals and organizations currently use. This is where “secure-by-design” technology is urgently needed. 

In the current system, tech companies create and sell technology that leaves users to contend with suboptimal solutions to their own security needs. However, as the name suggests, secure-by-design technology is created with privacy and security and embedded into a data-file from its origination to its expiration. 

CISA Director Easterly noted the importance of this approach in her address, pointing out that “… ultimately, such a transition to secure-by-default and secure-by-design products will help both organizations and technology providers: it will mean less time fixing problems, more time focusing on innovation and growth, and importantly, it will make life much harder for our adversaries.”

For now, the vast majority of ubiquitous security solutions are simply bandages over the inherent flaws of digital networks. However, a better, more fundamental type of cybersecurity does exist. 

Self-Protecting Data and Zero-Trust Security

Whether or not new regulations will compel the technology industry to create fundamentally more secure systems in the future, sensitive data — currently stored in digital spaces — already faces more threats than ever before. 

To date, the concept of perimeter security has been the de facto standard for data security. With the advent of the internet, securing networks has become a greater priority, and reliance on tools such as IP address verification and multi-factor authentication has only increased. Although relatively mature, these methods still serve as the primary ways in which most companies attempt to ensure that private information stays private. 

While perimeter security continues to serve an important purpose in protecting secure files, this form of traditional data protection is fundamentally flawed. When an organization’s defense relies purely on perimeter security, identifying and addressing vulnerabilities becomes a game of whack-a-mole between hackers and network administrators. 

Both conceptually and in practice, Zero-Trust security is a revolution. Rather than rely on a series of firewalls and trust that those with access are legitimately allowed to be there, Zero-Trust security protects data by demanding continuous authentication from users. Meanwhile, self-protecting data protocols — unlike perimeter security — are designed to give data files the ability to protect themselves from creation. 

Sertainty

As a leader in self-protecting data, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself. These protocols mean that even if systems are compromised or accessed from the inside, all data stored in them remains secure. 

At Sertainty, we know that the ability to maintain secure files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing self-protecting data solutions that evolve and grow to defend sensitive data. Open-source security breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be. 

AI Optimization and Anonymization

Posted on by Nicole Tidwell

Today, artificial intelligence is no longer the far-off dream it once was. Tools like Midjourney, ChatGPT, and others have taken off in the last year, bringing with them a barrage of questions.  Many cybersecurity experts, and those entrusted with handling sensitive information, have pegged data privacy as the likeliest potential threat that these programs pose to organizations. 

The capabilities of AI are surmounting daily. Cybersecurity risks are mounting in step. From the first moment an AI Engine is optimized, it starts processing datasets. Partly because of this, effective data anonymization has become critical due to various compliance regimes and consumer protection laws. Companies hoping to utilize the power of artificial intelligence must factor in which datasets, audiences, and business problems it seeks to ascertain their predictions. 

What Is AI Optimization? 

Before testing an AI program, it must be optimized for its intended application. While, by definition, these programs are always learning, the initial training and optimization stage – which is defined by Volume, Variety, and Variance, is an essential step in the AI development process. 

There are two modes of AI training: supervised and unsupervised. The main difference is that the former uses labeled data to help predict outcomes, while the latter does not. 

The amount of data available to AI dictates whether developers can extract inputs to generate a significant and nuanced prediction in a controlled environment. Depending on data accuracy, developers will intervene and recast an existing outcome into a general output and reiterate the unsupervised processing w for better quality control and outcome. 

Supervised Learning

In this context, labeled data refers to data points that have been given pre-assigned values or parameters by a human. These human-created points are then used as references by the algorithm to refine and validate its conclusions. Datasets are designed to train or “supervise” algorithms to classify data or predict outcomes accurately. 

Unsupervised Learning

While no machine learning can accurately occur without any human oversight, unsupervised learning uses machine learning algorithms to analyze and cluster unlabeled data sets. These algorithms discover hidden patterns in data without the need for human intervention, making them “unsupervised.” 

While more independent than supervised learning, unsupervised learning still requires some human intervention. This comes in the form of validating output variables and interpreting factors that the machine would not be able to recognize. 

Data Anonymization in Machine Learning

The majority of machine learning advances of the past three decades have been made by continuously refining programs and algorithms by providing them with huge volumes of data to train on. ChatGPT, one of the most popular AI platforms today, is an open-source chatbot that learns by trolling through massive amounts of information from the internet. 

For all of their impressive capabilities, however, AI programs like ChatGPT collect data indiscriminately. While this means that the programs can learn very quickly and provide comprehensively detailed information, they do not fundamentally regard personal or private information as off-limits. For example, family connections, vital information, location, and other personal data points are all perceived by AIs as potential sources of valuable information. 

These concerns are not exclusive to ChatGPT or any other specific program. The ingestion of large volumes of data by AI engines magnifies the need to protect sensitive data. 

Likewise, in supervised machine learning environments, anonymization for any labeled data points containing personal identifiable information (PII) is key. Aside from general concerns, many AI platforms are bound by privacy laws such as HIPAA for health-related data, CCPA legislation in California, or the GDPR for any data in the EU. 

Failing to protect the anonymity of data impacted by these laws can result in steep legal and financial penalties, making it crucial that anonymization is properly implemented in the realm of AI and Machine Learning. 

Pseudonymization vs. Anonymization

When discussing data privacy, the word anonymization is almost always used, but in reality, there are two ways of separating validated data points from any associated PII. In many cases, rather than completely anonymizing all data files individually, PII is replaced with non-identifiable tags (in essence, pseudonyms). 

Perhaps the most famous large-scale example of this is blockchain technology. While personal data such as real names or other PII are not used, in order for the record-keeping chain to function, all data for each user must be linked under the same pseudonym. While some people consider this to be sufficiently anonymous for their purposes, it’s not as secure as true anonymization. If a pseudonym is compromised for any reason, all associated data is essentially free for the taking. 

True anonymization, on the other hand, disassociates all identifying information from files, meaning that the individual points cannot be linked to each other, let alone to a particular person or parent file. 

Because of this, many security experts prefer to avoid the half-measure of pseudonymization whenever possible. Even if pseudonymous users are not exposed by error or doxxing, pseudonymized data is still vulnerable in ways that fully anonymized data is not. 

Already, some AIs are becoming so sophisticated that they may be able to deduce identities from the patterns within pseudonymized datasets, suggesting that this practice is not a secure replacement for thorough anonymization. The more data algorithms are trained on, the better they get at detecting patterns and identifying digital “fingerprints.” 

Other AI-Driven Anonymization Scenarios

In the current landscape of ever-more-capable machine learning, the value of proper data anonymization is greater than ever. Aside from the vulnerabilities within AI-driven frameworks, external threats driven by digital intelligence present new challenges, as well. 

For one thing, artificial intelligence is able to exploit technical loopholes more effectively than human hackers. But beyond that, AI is also increasing threats targeted at social engineering. Recently, users found that ChatGPT was able to generate phishing emails that were notably more convincing than many human-generated attempts. This will undoubtedly lead to increasingly sophisticated attempts to access private data. As such, new tactics must be employed to properly secure and anonymize data before it becomes exposed to artificial intelligence.

Anonymized Smart Data with Sertainty

Sertainty’s core UXP Technology enables Data as a Self-Protecting Endpoint that ensures the wishes of its owner are enforced. Sertainty’s core UXP Technology will also enable developers working within AI environments such as ChatGPT to maintain ethical and legal privacy with self-protecting data. Rather than attempting to hide PII and other sensitive data behind firewalls, Sertainty Self-Protecting Data files are empowered to recognize and thwart attacks, even from the inside. 

As a leader in self-protecting data, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself in today’s digital world. These protocols mean that if systems are externally compromised or even accessed from the inside, all data stored in them remains secure. 

At Sertainty, we know that the ability to maintain secure files is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs. 

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing self-protecting data solutions that evolve and grow to defend sensitive data. With the proliferation of human and AI threats, security breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be.

Could Zero-Trust Security Prevent Famous Data Breaches?

Posted on by Nicole Tidwell

Many security systems claim to be trustworthy, but when it comes to data security, few things are more important than real-world results. Ever-evolving claims of improved interfaces and threat detection software, “next-generation” systems, and many other promising developments, have been around for as long as we have been using computers. Yet, despite these claims, major data breaches occur all the time. Sophisticated infiltration methods match or exceed the pace of conventional security development, and social engineering and phishing scams are increasingly prevalent. 

While looking to the future is crucial to creating better data privacy solutions, security experts begin by examining the past. New systems have to not only provide solutions for emerging problems but address historic threats with meaningful changes. 

Types of Data Security

While there are many different methods and tools used to protect data, most of these measures are aimed at achieving one of two goals: keeping malicious actors out of private data systems, and ensuring that organizations are protected in the event of a breach. 

The first and most common focus in data protection is to create a secure storage environment. Tools for securing databases can include physical hardware security, passwords, firewall, proxy servers, user authentication, and more. All of these together form what is commonly referred to as perimeter security. Data destruction and proper sanitization of old devices can also play a role in protecting the integrity of data centers. 

While perimeter security is aimed at keeping criminals out, however,  traditional digital security is more reactive and perpetuates the vulnerabilities. Data backups and other redundant systems do help a company recover information in the event of ransomware and other attacks. However, it is always preferable to prevent attacks in the first place. To blaze new trails in the creation of cutting-edge data privacy measures, such as Zero-Trust methodologies, are a must if we are to preempt cyberattacks. 

Revisiting Recent Data Attacks

Perimeter security and data backups are standard measures, but neither provides a fully-integrated and comprehensive solution. This is evidenced by the fact that all of the organizations discussed below employed these methods and still suffered breaches. 

Zero-Trust protocols, on the other hand, prevent hackers from gaining the power to steal any sensitive data, even if outsiders do find a way past corporate firewalls — or are based on the inside. To understand how much of a difference Zero-Trust can make, let’s examine some of the highest-profile data breaches of the last decade and assess whether or not Zero-Trust security could have prevented these attacks. 

Yahoo

Over the course of two instances, Yahoo suffered the largest recorded data breach to date. Two attacks, one occurring in mid-2013 and the other in late 2014, were belatedly reported by the company in 2016. The breaches were accomplished using cookie-based attacks, which allowed hackers to enter the system as authenticated users. This attack has been largely attributed to “state-sponsored” agents (with many pointing fingers at the Russian government). 

Overall, over 3 billion user accounts were affected by the breaches. The fallout from these attacks not only led to class action lawsuits but also reduced the acquisition price of the company by Verizon by $350 million. 

SolarWinds

A more recent example of a high-profile breach occurred in 2020, when SolarWinds, a major US information technology firm, was the subject of a sophisticated cyberattack. Hackers broke into SolarWinds’ system and added malicious code that was later sent out as part of a routine update to clients of SolarWinds. Once installed, hackers were able to gain access to all manner of sensitive information in those customers’ own systems, including US government agencies like the Department of Homeland Security and the Pentagon. 

Facebook/Meta

Meta is no stranger to large-scale data breach incidents. The most recent known attack on Facebook was revealed in 2021 when private data from 533 million user accounts appeared on a public internet forum. While the attack was dismissed by Meta as the result of Open-Source Intelligence (OSINT) scraping, it was later revealed that hackers had accessed the information by exploiting vulnerabilities in Facebook’s Contact Import feature. This followed a June 2020 incident where Facebook accidentally shared private user data with third-party developers. 

Truly Secure Data with Zero-Trust

While each of these attacks was achieved using different methodologies, the common thread between them all (and most other data leaks) was in hackers finding a way to access private databases. This access could be the result of compromised user credentials, such as, in the case of Yahoo, code attacks on client transmission and patching (i.e., SolarWinds), system loopholes (Facebook), or even simple mistakes. 

The findings suggest that regardless of which method is used to gain entry, the real damage is done once malicious parties are inside the security perimeter. Even if backups are used to prevent data destruction or ransom, the damage of leaked private information is irreversible. 

Both, conceptually and in practice, Zero-Trust addresses data privacy’s greatest weaknesses. Rather than relying on security perimeters  – with the assumption that users within a system have the right to access its information, Zero-Trust security enables data files to protect themselves through independent verification. In a Zero-Trust security framework, users are continuously verified and authenticated, ensuring that data remains secure even if the system is compromised. 

Zero-Trust Security from Sertainty

With heightened information security threats, securing sensitive data in all sectors is more crucial than ever. Traditional perimeter security is becoming increasingly inadequate in the face of smarter, more motivated attacks. 

Sertainty has redefined how information is protected to ensure data privacy even where firewalls fail. Using cutting-edge protocols and embedding intelligence directly into data files and datasets, Sertainty leverages proprietary processes that enable data to Govern, Track, and Defend itself. These protocols mean that the data remains secure even if systems are compromised.

At Sertainty, we know that data is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be Intelligent and Actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs.

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing Self-Protecting Data solutions that evolve and grow to defend your crown jewels. Instead of focusing on your network’s inherent shortcomings, we enable you to safely and confidently embrace the potential of a new online-oriented world. Data breaches may be inevitable, but with Sertainty, privacy loss is moot.

The Implications of International Tensions on Cybersecurity

Posted on by Nicole Tidwell

As international tensions rise around the globe, experts in all areas of security are taking a closer look at data protection. While cybersecurity threats are an ever-present risk, increasing international tensions have led to the emergence of various other threats, including transnational terrorism and the use of chemical and other unconventional weapons.

The ensuing chaos from the increase in international tensions opens the doors for opportunistic hackers and cybercriminals to wreak havoc in vulnerable regions worldwide. Even in areas not in direct conflict, instability has presented challenges in keeping government and organizational data safe in increasingly at-risk environments.

Rising Overseas and Domestic Threats

The war in Ukraine, Chinese incursions into Taiwan, continuing Iranian-US tensions, and various other emerging potential issues have opened doors for all cyberattacks.

As recently as December 2022, the Center for Strategic and International Studies identified potential spyware hacks of US government employees, including diplomats in multiple countries. In the previous month, the CSIS identified 12 different incidents where the US, Ukrainian, Polish, Bahraini, Pakistani, and numerous other governments were targeted by cybercriminals.

Although many of the attacks reported by the CSIS come directly from foreign entities, data breaches can come from anywhere, and accessing confidential, vulnerable information can impact a country’s operations or wreak havoc on critical infrastructure. The number of nation-state cyber attacks against critical infrastructure has doubled in the past 12 months. 

In late 2022, the Danish State Railways’ network was temporarily shut down by hackers. However, in 2021, an even more powerful attack against the Colonial Pipeline cut off oil supplies to a large section of the eastern United States. While neither of these attacks appeared to be the work of hostile governments, as tensions rise, so does the potential for damage from similar breaches. 

When it comes to threats against intelligence data gathered by government agencies, the dangers can sometimes be exponentially more dangerous. While direct attacks against critical assets have immediate, tangible consequences, the sensitive nature of national intelligence data means that breaches can have cascading effects. Not only do intelligence data breaches potentially endanger the lives of operatives currently in foreign countries, but the revelation that intelligence operations are ongoing can also justify more direct actions. 

In some cases, information gathered and the methods by which it was acquired can have catastrophic effects on international relations. When tensions are already high, volatile data can be the final straw that dismantles international relations when compromised. Even friendly countries can find themselves at odds over foreign agencies’ methods of collecting data. Because of these factors, securing intelligence data takes on particular importance during times of rising international tensions, even if the countries in question are not directly in conflict with each other. 

Another genuine factor that makes securing intelligence data particularly critical is the potential for harm from compromised internal sources. Whether an operative leaks data themselves or is unintentionally compromised, it can devastate national security or national trust. Examples of these security compromises include the WikiLeaks release of 2010 and the reveal of the PRISM program. 

Challenges to the Private Sector

While the threats to government or infrastructure assets may be the most immediately apparent, data within the private sector can also see increased incidences of targeting during times of international tension or conflict. In addition to purely profit-motivated attacks like the Colonial Pipeline, governments may encourage hackers to after businesses in other countries. Hacking businesses internationally can be a strategic move to disrupt industry during wartime or destabilize other countries’ economies to their advantage. 

Additionally, the increased attacks can compromise sensitive information between the public sector and private contractors, as demonstrated by major security breaches at General Dynamics, Boeing, and Raytheon in the United States in recent years. By exposing private and public security vulnerabilities, international adversaries can access anything from personal information to blueprints for thermonuclear warheads. 

Responding to Threats with Truly Secure Data

With heightened global tensions, securing sensitive data in all sectors is more crucial than ever. Traditional “perimeter security,” which protects data by keeping outsiders from accessing a system, becomes increasingly inadequate in the face of motivated attacks. 

In many cases mentioned above, compromised passwords and user information were to blame for breaches. Even when attacks take on more sophisticated forms of cyberattacks — such as the DDoS attacks against the Italian and Finnish governments and several major US airports in 2022 — attempting to secure sensitive information with traditional perimeter security is inadequate.

Both conceptually and in practice, Zero Trust addresses data privacy’s greatest weaknesses. Rather than relying on a series of firewalls and assuming that users within a system have the right to access information stored on the server, Zero Trust security enables data files to protect themselves through independent verification. Through a Zero Trust security framework, users are continuously verified and authenticated — ensuring that data remains secure even if the system is compromised. 

Integrate a Zero Trust Architecture with Sertainty

Sertainty has redefined how information is protected to ensure data privacy even where firewalls fail. Using cutting-edge protocols and embedding intelligence directly into data files and datasets, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself. These protocols mean that the data remains secure even if systems are compromised.

At Sertainty, we know that data is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs.

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing Self-Protecting Data solutions that evolve and grow to defend your crown jewels. Instead of focusing on your network’s inherent shortcomings, we enable you to safely and confidently embrace the potential of a new online-oriented world. Data breaches may be inevitable, but with Sertainty, privacy loss is moot. 

Ignore These Rising Cybersecurity Threats at Your Peril

Posted on by Nicole Tidwell

As computer systems become more complex and interconnected, the potential for devastating data breaches also grows. Industry leaders and security experts recognize that to stay safe, data protection systems need to be one step ahead of hackers constantly. With the rapid development of new technologies, keeping track of emerging cybersecurity threats is more challenging and vital than ever before. 

Whilst a hacker’s targets and methods constantly change, current trends point to the threats we’re most likely to face. Hence, we have identified four growing cybersecurity threats to be sensitive to in the coming year. 

Attacks on Critical Infrastructure

Some of the most potentially devastating and escalating new cybersecurity dangers are aimed at critical infrastructure systems and public works worldwide. In 2021, the Colonial Pipeline fell victim to a crippling ransomware attack. The hack infiltrated some of the pipeline’s digital systems, shutting it down for several days, which compelled President Biden to declare a state of emergency. This cyberattack was deemed a national security event due to the shutdown of pipelines moving oil from refineries to industrial markets. This shutdown affected consumers and airlines along the East Coast. 

Consequently, this cyberattack garnered substantial public attention due to a potential contagion effect. Attacks targeting public infrastructure will take out essential systems, such as hospitals, water facilities, electricity, and energy production, and are often referred to as “killware” for their ability to cause disruption leading to real-life deaths. 

Access to Crypto Wallets

While the blockchain technology that powers cryptocurrencies is often lauded as “incorruptible,” there are a number of very real emerging threats aimed at cryptocurrency users. While the blockchain is not particularly vulnerable to attacks due to its decentralized nature, Bitcoin private keys, associated addresses, and crypto wallets can all be compromised by malware, allowing hackers to deplete accounts. 

These malicious programs are often delivered using classic phishing scams. Emails containing attachments (such as a Word document) that can execute macros to run the programs are sent to unsuspecting users. Similarly, fake Amazon gift cards, another phishing favorite, are being rigged with Remote Access Trojan (RAT) programs that steal crypto wallet information by keylogging and taking screenshots of the victim’s computer. 

Threats to Linux Systems

Historically, users have considered the Linux operating system to be safer from cyberattacks than other operating systems. Hackers have generally left Linux users alone, but there has been a significant rise in attacks on Linux systems. Unlike Windows, which is a targeted OS system, Linux does not have the support or proper patching capabilities to provide its users with the confidence that incoming cyber threats will be countered or remediated. The knowledge basis regarding how to deal with cyber threats is almost non-existent. 

What will aggravate matters is the development of a Windows Subsystem for Linux (WSL) in Windows 11. This will make Linux systems vulnerable to Windows attacks and vice-versa. 

In addition to being less understood, threats to Linux systems can also target more vulnerable areas than other types of attacks. Because of its relatively specialized nature, Linux is often utilized on the “back end” of businesses. It is often used to manage critical business and IT processes, making breaches to these systems particularly worrying. 

For example, many Internet of Things (IoT) systems and devices run on the Linux infrastructure. IoT devices have become less niche and will play a vital role in economic growth. Furthermore, Linux environments often have valuable data like Secure Socket Shell (SSH) credentials, certificates, applications usernames, and passwords, and are in need of protection from adversarial activities. 

Widening Network Edges 

Even as most governments and companies move away from COVID-19 safety protocols, the number of people working remotely has been steadily increasing. While accessibility is generally a positive feature, remote work means that there are more devices and locations needing to access databases, increasing what is known as the “network edge.” Workers’ at-home devices are often more vulnerable to attack than those in an office, and hackers have been taking full advantage of these new doors into private networks. 

Likewise, “bring-your-own-device” policies further increase the network edge by opening networks to an even wider variety of devices. This creates new opportunities for hackers to gain entry to information by compromising employees’ personal computers and phones rather than resorting to attacking a company’s system directly. 

Managing Cybersecurity Threats with Sertainty

In the face of these (and other) emerging cybersecurity threats, securing sensitive data is more crucial than ever. Traditional “perimeter security,” wherein data is protected by keeping outsiders from accessing a system, becomes increasingly inadequate as connectivity increases. With information becoming ubiquitous and available to users anywhere, the process of granting access to approved parties becomes a difficult balance between security and convenience, often leaving numerous doors open to malicious actors. 

Sertainty has redefined how information is protected to ensure data privacy even where firewalls fail. Using cutting-edge protocols and embedding intelligence directly into data files and datasets, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself. These protocols mean that even if systems are compromised, the data remains secure.

At Sertainty, we know that data is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs.

As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing Self-Protecting Data solutions that evolve and grow to defend your crown jewels. Instead of focusing on your network’s inherent shortcomings, we enable you to safely and confidently embrace the potential of a new online-oriented world. Data breaches may be inevitable, but with Sertainty, privacy loss is moot.