Tag: cybersecurity industry

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. 

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.

Defense-In-Depth: The Future of Data Security

Posted on by Nicole Tidwell

In a digital world brimming with cyber threats, adopting a “defense-in-depth” approach is a vital weapon in your arsenal against potential breaches and vulnerabilities. Rather than fixing security issues after the fact, defense-in-depth focuses on crafting technology with multiple layers of security included at each stage of development and implementation. This proactive approach has become imperative in the cybersecurity landscape, reshaping how we build and fortify our digital systems.

In this ever-evolving landscape, traditional perimeter-based security models often falter. Hackers exploit vulnerabilities, slipping through the gaps of systems designed to trust too much. While the idea of addressing security threats at the development level is not fundamentally new, the measures coded into many programs are themselves imperfect, leading to a false sense of security from users and developers alike. 

This is not to say that defense-in-depth has to be predicated on more layers of the same flawed technologies. On the contrary, reimagining this framework has led to revolutions within the cybersecurity world. 

Understanding the Value of the Defense-In-Depth Approach

At its heart, defense-in-depth embodies a philosophy where security is not an afterthought, but rather an integral part of the creation process. The core principles revolve around integrating security measures right from the inception of a technological solution. By baking security into every layer, from design to deployment, we create a robust and fortified environment to withstand potential threats.

Secure-by-Design Technology

Often, the far-reaching benefits of a combined defense-in-depth approach and DevSecOps lead to technology referred to as “secure by design.” As the name suggests, utilizing this approach entails considering security from the outset, minimizing vulnerabilities, and reducing the attack surface that malicious actors can exploit. This, in turn, leads to more resilient systems, enhancing the overall cybersecurity posture of organizations. Trustworthiness and reliability become hallmarks of the technology, inspiring user confidence.

Secure IoT Devices and Smart Systems

Secure-by-design technology does not have to refer exclusively to data storage solutions, either. This thinking can be applied to a wider variety of technologies, such as IoT devices and smart systems. While the potential vulnerabilities present in these systems are often overlooked, a true defense-in-depth approach accounts for all threat vectors, including seemingly innocuous peripheral technologies. 

Elements of a Defense-In-Depth Approach

Integrating security throughout the development lifecycle means that every step is taken with potential threats in mind. Secure coding practices ensure that vulnerabilities are not inadvertently introduced during the coding process. 

DevSecOps

In order to fully embrace a defense-in-depth system, security must be part of any discussion from the earliest stages of development. DevSecOps merges development, security, and operations into a unified approach. It emphasizes continuous security testing and collaboration throughout the software development lifecycle. DevSecOps is all about identifying vulnerabilities early and addressing them in real time, ensuring that security is not compromised while speeding up development.

Other Elements of Defense-In-Depth Security

As the development and implementation of security protocols progress, new layers are added at each step. For example, threat modeling identifies risks and guides decisions, while continuous security testing identifies and addresses weaknesses before they’re exploited.

Other elements commonly incorporated into a secure-by-design model include conventional perimeter security protocols and encryption safeguards. Perimeter security in a defense-in-depth system often entails more than simple passwords. More comprehensive verification methods can include a combination of elements, such as security questions, physical security keys, and biometrics. 

On the transit side, encryption safeguards sensitive data, both at rest and in transit, rendering it useless even if intercepted. Some seemingly secure transmission methods are erroneously considered to be an acceptable form of data security, but in reality, technologies like blockchain bring their own set of potential pitfalls — and should not be solely relied upon in place of a thorough defense-in-depth approach.

The Future of Secure-by-Design Technology

While all of the above elements are crucial aspects of defense-in-depth, each step still leaves gaps that can be exploited by knowledgeable, committed hackers. This is where zero-trust data security and self-protecting data solutions come into the picture. Rather than simply adding another layer of security, Sertainty self-protecting data technology introduces an entirely new type of data protection to a defense-in-depth framework. These technologies redefine data security, focusing on safeguarding data itself and ensuring its integrity in the face of ever-evolving threats. 

Unlike conventional security measures, zero-trust access protocols and data-level security solutions ensure that data remains protected from all sources, regardless of how files are accessed. This approach reshapes the data security landscape, ensuring that sensitive information remains under an impenetrable cloak, safeguarded against breaches and unauthorized access.

The essence of Sertainty’s zero-trust data security technology lies in its proactive stance. It does not merely shield the perimeter; it safeguards the very data at the core of your digital ecosystem. This technology empowers data with the ability to defend itself, rendering it useless if intercepted or tampered with. Whether data is at rest, in transit, or being processed, Sertainty UXP lets developers give data its own security, regardless of the environment.

This technology brings a paradigm shift in how we view data breaches. Rather than relying only on barriers to keep threats out, Sertainty UXP’s zero-trust data security technology empowers data files to monitor and protect themselves. Even if an attacker gains access, the protected data becomes an enigma, rendering their efforts fruitless. This also means that insider attacks, which are virtually impossible to mitigate, are a non-factor. 

Embrace Truly Secure-by-Design Technology Solutions with Sertainty

As a leader in self-protecting data, Sertainty leverages proprietary processes to ensure 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. 

In an era where cyber threats continue to morph and infiltrate, Sertainty zero-trust data security technology shines as a sentinel of data integrity. As we gaze into the horizon of secure-by-design technology, Sertainty is committed to providing self-protecting data solutions that evolve and grow to defend sensitive data. Cyber threats may continue to advance, and security perimeter breaches 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. 

Securing Private and Intelligence Data

Posted on by Nicole Tidwell

When it comes to information security, no sector can be overlooked. Both private sector and intelligence data gathered by government agencies require care in their handling, storage, and transmission. And while there are a number of universally-accepted best practices for maintaining data confidentiality, the unique nature of information relevant to national interest necessitates additional measures. 


Much of the work of information security is the result of policy and training, but tools like the Sertainty Data Privacy Platform also play a central role in securing data in both the public and private sectors. 

What Is Intelligence Data?

Generally, intelligence data refers to any data gathered by intelligence operatives or agencies. This data can be collected for a variety of purposes, from predicting and mitigating potential threats to informing government policy and even military operations. This can include information about people, finances, transportation, infrastructure, or any other data that may be of use in a particular scenario. 

Often, the identities of the agents gathering the data, as well as the methods used, are highly protected. This amplifies the need for airtight privacy, as each step of the process must remain strictly confidential, even from other agents within the organization. 

Similarities Between Private and Intelligence Data Security

At its core, data privacy is a universal concern. Any organization, whether public or private, that gathers information relies on a certain level of exclusivity in order to make that data useful. Not only is secure data vital to making informed decisions, but it can also provide a business edge over the competition. Likewise, in many industries, information security protocols are required in order to obtain (and maintain) the licenses and certifications needed to conduct business. 

When it comes to creating an organizational security policy in the modern world, there are a number of factors that need to be accounted for — whether you’re protecting private or intelligence data.

Defense-in-Depth Safeguards

The foundation of any organization’s security plan, regardless of its industry, can’t be one-dimensional. A defense-in-depth approach combines multiple levels of security protocols into a single, cohesive privacy plan. This can include elements such as firewalls, encrypted networks, security training, and any other layer of protection. 

Two-Factor Encryption

Another vital piece of the puzzle in a comprehensive security plan involves user authentication. Users may be familiar with the process of imputing a code received on a separate device, but two-factor authentication can include even more secure measures, such as physical access keys, biometric scans, and answering security questions. 

Remote Access Protocols

Unlike in the past, virtually all data storage networks need to be accessible to users outside of a specific office or closed LAN. This can apply to work-from-home employees and intelligence field operatives alike, and ensuring that only approved users can enter the system is vital. Furthermore, both of the above concepts around safeguards and encryption can and should play a role in how remote access protocols are designed. 

Special Considerations for Intelligence Data

The above represent some of the most common security measures, all of which can be found in many civilian applications. Others, however, are less common outside of high-sensitivity industries. 

There are two primary factors that make intelligence data different from other private information. For one, the potential implications of an intelligence data leak are far greater than those in any private company. Consequences can be felt on a national or even global level. This level of significance means that there is absolutely no room for mistakes of any kind. 

The second factor is the need for multi-level confidentiality. As we mentioned above, in addition to the data itself, the identities, locations, and methods by which it was obtained are often extremely sensitive. Due to the need for internal privacy, conventional perimeter security is often insufficient. 

Let’s take a look at some of the unique ways in which intelligence data can be protected, as well as examine the value of Zero-Trust security. 

Compartmentalization

Perhaps the most critical element of intelligence data security strategies involves keeping different sources and stores of information separate from each other. The reasons that compartmentalization is so important are twofold. Firstly, even if one data store is compromised, compartmentalization ensures that the breach is contained to that single, limited store. The other primary benefit is that users have less potential to interact with each other, allowing for an increased level of anonymity. 

Asymmetric Access

Rather than relying on a secured messenger application, sending sensitive communications in the intelligence world is often handled using asymmetric access. In these types of systems, two virtual keys are needed to receive messages: one public key, findable within a database, and one private key, accessible to only a specific designated user. Sending messages can be done using a public key, but each user’s private key is needed to open the messages intended for them.

Sensitive Compartmentalized Information Facilities

In the most sensitive cases, extremely important data can only be accessed within the confines of a Sensitive Compartmentalized Information Facility (SCIF). To gain access to the information stored in these physical locations, users must be pre-screened and authorized, as well as pass through a series of checks and authentications. Once inside, they can access and discuss the information stored there but cannot send or receive any communications while they are in the facility. 

Zero-Trust with Sertainty

In virtually every area we’ve discussed, traditional network security falls short in a number of key areas. Insider threats, human error, and a number of other inevitable vulnerabilities can leave information of all kinds open to malicious actors. Unlike other technology platforms, which are fundamentally limited in their scope, Sertainty data protection is ideal for both intelligence data and private applications. 

Self-protecting data from 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. 

Cyberattacks Are Targeting Digital Supply Chains More Than Ever — What Does It Mean for Your Business?

Posted on by Nicole Tidwell

The 2020s See a Dramatic Increase in Phishing Attacks

Posted on by Nicole Tidwell

What Is a Zero Trust Model, and Why Is It Becoming the Data Security Standard?

Posted on by Nicole Tidwell

The Increasing Scrutiny on Cybersecurity in Healthcare

Posted on by Nicole Tidwell

Cybersecurity: Trends and Statistics in 2021

Posted on by Nicole Tidwell