DevSecOps: The Future of Built-In Cybersecurity

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

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

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. 

The Quantum Leap: Why Data-Level Security Is the Vanguard Against the Next Wave of Cybersecurity Threats

In the ever-evolving theater of cybersecurity, the proliferation of quantum computing presents a formidable challenge to our current defense-in-depth strategies. While conventional data security has traditionally provided a layered defense against intrusions, it is largely predicated on the computational limitations that quantum computers are expected to obliterate. The stark reality is that the standard security algorithms that guard much of our most sensitive data, today, could be effortlessly decrypted, tomorrow, using quantum machines. 

The solution to this looming tidal wave is not in fortifying the walls of our sandcastles, but in looking toward a new paradigm enshrining data security. Henceforth, despite the still-nascent nature of these risks, the technology required to address quantum security threats actually exist. True, whilst industry giants like Microsoft are only beginning to discuss the nature of these threats, the military, enterprises and leaders in cybersecurity are looking toward a data-level security approach such as exemplified by the Sertainty Self-Protecting Data technology. The novelty behind Self-protecting data encryption is that it allows each data file to become a cryptographically micro-perimeter and secure object that can defend itself, irrespective of the system it resides in. 

This type of self-protecting data that can resist quantum threats was recently discussed by my colleague Dr. Behzad Nadji in his whitepaper, “Quantum Computer Threats Against PKI Data Security and a Digital-ID Based Self-Protecting-Data Solution.” 

The similarity between quantum-enabled security threats and the recent surge in AI-enabled cybersecurity breaches perfectly illustrates how self-protecting data has the potential to address quantum threats. Like quantum encryption-breaking, machine learning algorithms can be commanded to simulate a“brute force” attack in which the sheer computational might foreseen in a quantum computer will break traditional cryptographic defenses in concert with AI algorithms that will identify the vulnerabilities that apply Shor’s Law. 

Likewise, generative AI’s rapidly growing capability to produce social engineering attacks — creating more sophisticated phishing attempts that can fool the most vigilant — is a precursor to the scale of disruption quantum computing will bring on the classical computing paradigm premised on Moore’s law. 

A data-level security approach addresses today’s Quantum Encryption and AI challenges by embedding a symmetrical – lattice-like protection scheme within the data itself. This implies that even if a quantum computer could process intercepted data, or an AI  fakes legitimate access of a user, the data will remain secure. The reason is that the Sertainty Self-Protecting Data mechanism requires authentication at the data layer, which is a significant departure from perimeter-based security models.

Thus, the data becomes its own sentinel, capable of making decisions about who can access it, when, and under what circumstances. This is akin to a biometric system that not only knows who you are but also understands the context of your request. If the context is inappropriate — say, during an AI-driven brute force attack or a quantum-decryption attempt — the data remains locked.

As we stand on the precipice of a quantum future, it is clear that a paradigm shift in our approach to cybersecurity is not just warranted but essential. The Sertainty approach to data-level security provides an archetype for the quantum age, ensuring that data can stand resilient against the foreseen formidable capabilities of quantum computers and AI-driven cyber threats. We must transition from defense-in-depth to data-in-depth, focusing on making the data itself an active participant in its defense. This is not merely a strategic choice; it is the cornerstone upon which the future of digital security must and will be built. 

About Amir Sernhell

Amir Sternhell, Chief Strategy Officer of Sertainty Corporation, has thirty years of experience in the Global IT and Corporate Learning Industries. Amir spearheads the strategic direction to set “Self-Protecting-Data” as a new global standard in the data protection space. He oversees Sertainty’s strategic thrusts and partnerships into Enterprises, Critical Infrastructure, and Defense.  

He has held senior positions whilst working for a leading IT company – close to two decades – that represented Harvard Business Publishing in the Latin American markets for fifteen years, whereby he became a Chief Learning Officer as well as a pioneer in the Corporate Learning world and was the first to deploy over fifty blended programs on Leadership, Innovation, and Creativity utilizing content from Harvard Business Publishing as means to generate ‘Leadership at every Level’. He was awarded the Most Valuable Distributor Award three times. 

Amir founded the first non-profit organization that assisted Israel’s burgeoning incubator system, later becoming the Vice Chairman of the American-Israel Chamber of Commerce and Industry, overseeing its High-Tech initiatives for two decades. Amir currently sits on multiple Advisory Boards and continues to help execute groundbreaking initiatives in the Tech Industry. He is a Keynote and Panelist at major industry and cybersecurity events. 

Beyond Defense-in-Depth: Why It’s Time to Embrace Data-Level Security

As we enter a new age of cybersecurity threats, our defense practices need more than a simple tactical change — we need a strategic evolution that promises to streamline cybersecurity, reduce costs, and enhance protection. That’s why shifting from a reactive, perimeter-focused defense-in-depth strategy to a more proactive, data-centric security approach is becoming a matter of necessity. 

Defense-in-depth has been the bedrock of our cybersecurity strategy for decades, providing a sophisticated, layered approach to security. However, this model is fundamentally reactive, and as time has progressed, it has become increasingly complex and siloed. Because the defense-in-depth model operates on the premise that breaches will occur at the outer layers, it demands multiple fallbacks. While each layer has its role, the complexity and isolation of these systems can create gaps that savvy attackers exploit — including both malicious and inadvertent risks from insiders, who represent an increasing threat vector today. 

However, if data itself is our central focus, it becomes both the perimeter and the endpoint, behaving as an active participant in its own defense. When adopting this model, security measures are embedded within the data itself, ensuring that it remains protected regardless of its location — whether within the corporate network, in the cloud, or in transit to a partner site. 

Envisioning data as the new perimeter means recognizing that data traverses beyond the traditional bounds of enterprise control. It makes its presence known in the cloud, across devices, and through various networks. By embedding security controls directly within the data, we create a dynamic, mobile perimeter that offers protection wherever the data resides or travels. This approach ensures continuous protection and addresses the critical pain points of the private sector, where agility and responsiveness to threats are paramount. 

Simultaneously, viewing data as the new endpoint emphasizes the need for protection at the point of use. Whether it’s personal information or intellectual property, the data endpoint is where the value — and the vulnerability — lies. By encrypting data, we ensure that even if it falls into the wrong hands, its confidentiality and integrity remain intact. 

Acknowledging this, it’s time to recognize the role of data-level security in the coming age. This data-centric methodology offers a more streamlined and efficient security process, significantly reducing the need for extensive security teams and layers of protection. This approach also translates to a direct impact on organizations’ bottom lines — not only saving on costs but also on personnel and complexity, as well as eliminating the data silos that a conventional defense-in-depth approach inadvertently creates. These benefits are especially vital when the current cybersecurity landscape is marked by drastic increases in security spending and a shortage of qualified personnel. 

As the world shifts toward adopting a data-as-a-product (DaaP) approach to information, securing this product is paramount. This perspective is not limited to data-centric businesses but is a universal value across all sectors. A data-centric security approach is not just about defense but also about empowerment. This transformation anticipates and preempts emerging threats, such as those enabled by machine learning, and, in the near future, quantum computing, constructing a more intelligent, data-first line of defense. 

The transition to a data-level security approach represents a strategic reorientation that can simplify, secure, and streamline corporate cybersecurity. It’s a shift that addresses the current landscape of threats and the evolving regulatory environment, recognizing data as the invaluable asset that it is. It’s time for cybersecurity leaders to align themselves with this shift, to not only defend but to empower data to protect itself and, by extension, the enterprises that depend on it. 

About the Author

Jeff Snyder is a senior Sertainty Advisory Board member and cybersecurity expert, boasting over twenty years of experience. His career is marked by significant Cyber contributions to both federal agencies and the private sector. He has been instrumental in the strategic acquisition and growth of over 20 companies in the cybersecurity industry. 

Additionally, Jeff is a sought-after speaker regarding a spectrum of pressing topics, from the

Zero-Day Exploits: What They Are and How You Can Prepare

Zero-day exploits are among the most elusive and dangerous cyber threats in today’s digital landscape. These sophisticated attacks target undisclosed vulnerabilities, leaving organizations defenseless and scrambling for solutions. In this article, we will explore the world of zero-day exploits and their profound impact on data security. 

What Are Zero-Day Exploits?

Zero-day exploits refer to cyberattacks that take advantage of undisclosed software vulnerabilities. The term “zero-day” indicates that organizations and their developers have no time to prepare for these attacks, as the vulnerabilities are exploited before any patch or fix is available to the flaws. These exploits pose significant challenges to cybersecurity, as they leave victims defenseless against unseen threats.

Zero-day attacks emerged around 2006, due to the collaboration between the United States NSA and Israel’s 8200 Unit which berthed a 500Kb computer worm called Stuxnet. This worm featured a design and architecture that were not domain-specific and could be utilized for attacking modern SCADA and PLC systems. This made Stuxnet capable of infecting Iranian nuclear centrifuges that were enriching weapons-grade Uranium as part of its Nuclear program.

It was the first time that a Zero-Day cyber attack was used for military purposes. This opened the floodgates for competition in the cyber arena through en-masse weaponization of zero-day attacks as part of the military doctrine of China, Russia, Iran, and North Korea. Or, as an integral part of the Forward Defense activities of the US, UK, and Israel, to keep the cybersecurity arena from escalating further. 

Thereafter, the potential of zero-day exploits—whether by malicious organizations, nation-states and their proxies, or individual hackers—began to seep into the psyche and operations of the DoD and IT world. The threat of zero-day attacks have underlined the need to mitigate any software security vulnerabilities as soon as they are discovered. 

How Zero-Day Exploits Work

Zero-day exploits follow a well-defined technical process that malicious actors use to infiltrate systems. Attackers tirelessly search for undisclosed vulnerabilities, knowing that these are the keys to high-impact attacks. Once found, they skillfully exploit these weaknesses, gaining unauthorized access to systems, stealing sensitive data, or disrupting critical operations.

Identifying Zero-Day Vulnerabilities

Researchers and hackers use various methods to identify zero-day vulnerabilities. Vulnerability research involves analyzing software code to uncover potential weaknesses. Bug bounty programs encourage ethical hackers to report zero-day vulnerabilities in exchange for rewards. The dark web also plays a role, serving as a marketplace where hackers buy, sell, or trade information about undisclosed vulnerabilities.

The Implications of Zero-Day Exploits

The consequences of zero-day exploits can be devastating. Real-life examples have shown how these attacks compromise the security and privacy of individuals, organizations, and even critical infrastructure. The financial impact can be significant, with remediation costs and potential legal liabilities. Furthermore, the reputational damage resulting from a successful zero-day exploit can tarnish an organization’s image for years to come.

Significant Historical Zero-Day Exploits

While Stuxnet is perhaps the most widely-publicized example of a zero-day exploit, other threats of this nature have only increased in the nearly two decades since it first made waves. In fact, a 2022 report found that a shocking 40% of all zero-day exploits that happened between 2012 and 2021 happened in 2021 alone

Let’s take a look at some significant zero-day exploits from the last decade to better understand how these types of threats can affect your business. 

Yahoo (August 2013)

Though it’s been eight years since the Yahoo attack, this zero-day incident remains one of the most prominent to date. In 2016, the company revealed that more than 3 billion accounts had been accessed by hackers in the attack. In addition to exposing user data, the incident caused Yahoo’s value to drop significantly in the midst of a potential acquisition. 

LinkedIn (June 2021)

Another notable incident occurred in 2021 when LinkedIn reported that it had been hit by a zero-day attack that affected over 90% of its user base (700 million users). In this attack, a hacker scraped data by exploiting the site’s API. Before being taken down by law enforcement, the group responsible for CVE-2021-1879 publicly released a data set of around 500 million users. 

Microsoft (July 2023)

In July of 2023, Microsoft confirmed a shocking 132 security vulnerabilities across its product lines, including six confirmed zero-day exploits. One of these zero-days was remote code execution found within Microsoft Office and Windows HTML that could allow hackers to create Microsoft Office documents enabling them to perform remote code execution in victims’ devices.

While patches for significant exploits like these are typically quickly released, as of July 21st, Microsoft has yet to release a patch for CVE-2023-36884. The company is instead offering mitigation steps for affected users. 

Defense Strategies Against Zero-Day Exploits

Mitigating the risks posed by zero-day exploits requires a proactive approach to cybersecurity. Vulnerability management and prompt patching are essential in reducing the attack surface and limiting the window of opportunity for attackers. However, traditional security measures may not always be enough. 

Leveraging Self-Protecting Data for Zero-Day Exploit Defense

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. While firewalls and secure networks are essential elements of any complete information security plan, truly guarding data against all attacks requires Self-Protecting Data

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 data itself. 

Instead of database security being based on granted privileges to access the network directory where the file currently resides, Sertainty Self-Protecting Data (SPD) technology empowers the files themselves to protect themselves against malicious activity immediately. The Sertainty Data Privacy Platform 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. 

Zero-day exploits represent a constant and formidable challenge to data security. As cyber threats evolve, organizations must stay ahead by adopting proactive defense strategies. Sertainty Self-Protecting Data technology offers a powerful shield against the unseen dangers of zero-day exploits. By embracing innovative solutions and staying vigilant, we can fortify our data defenses and navigate the ever-changing cybersecurity landscape with confidence. Protecting our data is not just a matter of staying one step ahead — it’s a commitment to safeguarding what matters most.

Truly Secure Data with Sertainty

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. 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

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

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

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.

How Self-Protecting Data Creates Truly Secure Files

Technology has taken leaps and bounds forward in the last few decades. This growth has expanded our capabilities and access to computing power. As data applications have become more widespread and versatile, our reliance on secure files has also increased. 

Cybercrime has been quick to interject itself with the exponential growth of unstructured data files. Network computing today, whilst truly innovative, is replete with major attacks aimed at shutting it down. The motivation behind these breaches has ranged from simple thievery and greed to catastrophic acts of global cyberterrorism. Moreover, the Dark Web continues to be populated with tools and malware that make this onslaught continuous and dire. 

As much as both private companies and government agencies work to secure files and networks, hackers are never far behind. Often, the tools that make sensitive networks so accessible and valuable are also their Achilles heels. 

The Limits of Traditional Security

The vast majority of the most complex security systems operate on the same basic principle: to keep malicious actors or programs out of your secure files. Marketing claims notwithstanding, most of these systems approach cyber security issues with a similar method, almost invariably using some form of perimeter security. 

To date, the concept of perimeter security has been the de facto standard for data security, even predating the firewall. Even the earliest computers that operated on closed networks kept themselves secure by restricting who could use the computer terminal. This then advanced to dedicated user accounts and passwords. With the advent of the internet, securing networks became an even greater priority. Reliance on tools such as an IP address and verification and multi-factor authentication serve as the primary ways 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. 

Irrespective of how good your administrators are, ways into a system will always exist. Once a private system’s perimeter has been breached, users can do as they please. This means that not only are compromised credentials a threat, but conventional perimeter security systems are exceedingly vulnerable to inside attacks. 

How Does Self-Protecting Data Work?

Rather than simply trying to improve on inherently flawed concepts, self-protecting data is the result of rethinking our security fabric. As the name implies, the goal of self-protecting data is not simply to keep hackers out of your system but to create truly secure files. 

While the mechanisms of self-protecting data are extremely intricate, the fundamental concept is fairly straightforward. Instead of being left accessible to “approved” users, the files themselves are coded with the ability to recognize malicious activity and counter it immediately, regardless of who performed the action. 

Operating on a Zero-Trust basis connotes that basic perimeter security like password-protected logins becomes a first layer of defense rather than the sole source of protection for your files. Enhancing your defenses with the Sertainty Self-Protecting-Data (SPD) not only stops an outside actor who has infiltrated the system from wreaking havoc, but it also prevents insiders from creating chaos. 

Types of Threats to Secure Files

To better understand how SPD creates truly secure files, we must consider what attackers are attempting to accomplish. Let’s take a look at some types of attacks and see how SPD identifies and negates \ mitigates them. 

Ransomware

In ransomware attacks, hackers will create a program that has the ability to block access to secure files or a system, usually threatening to delete data if an organization does not comply with a specific set of demands. In a conventional security system, a user or program that has gained the ability to execute code within your network has the power to deploy malware in a system to exact ransomware. 

SPD files, however, are given the ability to recognize when a malicious program is attempting to gain control over it and block access to it whilst alerting system admins by themselves. Not only does this prevent the ransomware from harming secured files, but it can also provide valuable metadata about the attempt, giving insights needed to strengthen an organization’s security system further and factor continuity of operations to maintain resiliency. 

Social Engineering

Unlike “direct attacks,” where malicious programs are created to exploit a specific weakness in a security system, social engineering attacks attempt to trick employees or other legitimate users into compromising their credentials. These can come in the form of phishing emails or phone calls, malicious links, key tracking software, and other forms of trickery. 

Once they have captured the appropriate login credentials, hackers are free to do as they please within your system until you catch them and lock them out again. Because Sertainty SPD embeds a Zero-Trust framework within files, malicious actions are blocked and reported, even if they’re taken by a party with valid credentials but out of context and geographical location.  

Insider Attacks

Because insider attacks come from parties who already have legitimate access to a system, any form of perimeter security is, by definition, useless. But with the Sertainty SPD, even fully legitimate and “trusted” members of your organization are defended against by the files themselves. This not only prevents rogue parties from stealing or destroying valuable data, but it also protects against accidental actions that can harm your secure files. 

Truly Secure Data with 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. 

Is Blockchain Really as Secure as it Seems?

For nearly a decade and a half, cryptocurrency and the blockchain technology that powers it have played an increasingly central role in cybersecurity and online privacy discussions. Bitcoin and other cryptocurrencies have been touted as truly anonymous ways of storing and spending money, and popular perception remains, which is that blockchain itself is “unhackable.” 

While the idea of digital currency or decentralized data is not a new one, functioning blockchains are still relatively new. The technology became viable in 2008 when a person (or group of people) using the name ‘Satoshi Nakamoto’ introduced the first digital currency that addressed decentralization’s past issues by creating the first viable blockchain. Since then, various applications for blockchain technology have been developed, mostly due to its inherently incorruptible nature. 

How Does the Blockchain Work? 

Sometimes referred to as distributed ledger technology, a blockchain is a type of online database that maintains records in the form of “blocks” of information that are cataloged in chronological order. This creates a “chain” of data blocks, each representing an event in the history of the complete system. Each time a new transaction is completed, a new block is added, continuing the ledger of information. 

Blockchains come in two primary forms, public and private. In public chains, users from anywhere can join, becoming a part of the chain of nodes, sending and receiving transfers of data and currency that are then included in the chain. On the other hand,  private chains only allow users that have been granted permission to access transaction data. Both private and public chains can also be “permissionless” or “permission restricted,” depending on whether or not users within the network have the ability to validate transactions or merely utilize the existing nodes. 

It’s worth noting that blockchain technology can be used to send, receive, and track where files are sent. However, the actual data within the blocks remain private. The data itself is only accessible to the user(s) with the correct digital ‘keys.’ The databases where information shared using a blockchain is stored still have the same features and vulnerabilities, regardless of how securely that data may be shared.

A Reputation for Inherent Security

As we mentioned earlier, a common perception among those who use any form of blockchain technology is that this type of system is impenetrable. Like conventional digital ledgers, the record of events is intended to be permanent, with each block becoming unchangeable once it’s accepted into the chain. However, unlike traditional systems, blockchain data is stored across multiple nodes hosted in different locations. The wider the web of nodes spreads, the more fail-safes the system has. 

The result is a theoretically corruption-proof system. In theory, if a secure node (or nodes) were to be compromised, the rest of the blockchain would recognize the discrepancies and prevent false information from being accepted. 

Blockchain’s Limitations

While all of this makes large blockchains fundamentally more reliable than single-source records, no system is completely immune to threats. The dangers to the blockchain can come from users within a network or outside of it. These dangers must be considered before you put all of your faith into a system on reputation alone. 

51% and Sybil-Type Attacks

While the record of shared information is protected by the wide variety of verification data centers in the system, malicious actors can target the network itself. The two most obvious threats to blockchain networks come in for form of “51%” attacks and “Sybil-Type” attacks. 

During 51% of attacks, hackers attempt to generate enough data verification nodes to outnumber the number of legitimate nodes. If a single party can gain control of more than half of a blockchain’s nodes (hence the name), the information they present will be seen by the system as the ‘real’ record, and the previously existing, legitimate chain will be overruled.

Additionally, 51% of these attacks are only practical in smaller networks. Major blockchains, like Bitcoin, are far too vast for any one group to take control. Additionally, these attacks can be mitigated using a permission-restricted system so only verified users can create new nodes. 

Sybil-type attacks, so-called after a book of the same title, refer to an attack by users who attempt to create an overwhelming number of false transactions with false identities. These attacks flood the chain with unreliable information and overwhelm the system. Sybil-type attacks share some similarities with other blockchain threats, but they are easier to create in public chains. These attacks can be prevented if there is a high cost to create new accounts to discourage users from creating enough to disrupt the chain. 

Compromised User Accounts and Routing Attacks

Like with many digital systems, the greatest vulnerabilities of all come from the human component. While correctly moderated blockchains may be extremely resistant to intervention, users in the system are always vulnerable to phishing, RAT attacks, and other social engineering scams that jeopardize credentials and digital keys. 

Due to the impact of human error, data shared via the blockchain can be verified as coming from a legitimate source; however, there’s no guarantee of safety once it has reached its destination. Crypto wallets, private databases, and more can all still be breached by inside or outside actors.

Cryptocurrency Exchange Trustworthiness

If sending money over blockchain, users need to familiarize themselves with the crypto exchange. Although many tout the safety and security of the blockchain, using cryptocurrency for transactions isn’t safe as what was once alluded to. With the recent collapse of FTX and loss of $2 billion in user funds, businesses and individuals alike could be at the mercy of how these private organizations are handling both data and money. 

Truly Secure Data with Sertainty 

Regardless of the enhanced legitimacy of decentralized ledger systems, data breaches remain a significant concern for any conventionally-protected network. Utilizing a public or private blockchain can be one part of your data protection strategy. However, to guarantee that network breaches don’t leave you vulnerable, you must ensure that your data files are truly secure. 

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. 

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. Instead of focusing on your network’s inherent shortcomings, we enable our partners to safely and confidently embrace the potential of a new online-oriented world. Data breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be.

How “Bring Your Own Device” Policies Are Feeding the Rise of Mobile Threats

Driven by the shift to remote and hybrid work models, more and more people are using their personal devices for work purposes. A vast majority of Americans own smartphones, and many use those phones to access internal company documents and databases. But while this may be a convenient habit, it also introduces complex security risks.

Sensitive data is at a greater risk than ever before, with high-profile breaches making headlines. Understanding the threats to workers’ personal IT assets is vital in today’s connected landscape. As the proliferation of devices opens up potential network vulnerabilities, innovative security has to stay one step ahead of evolving digital threats. 

The Shift to BYOD 

Over the last decade, companies have been moving toward “Bring Your Own Device” policies, encouraging employees to use their own devices for work tasks. The onset of COVID-19 and the subsequent shift towards remote working has only increased this trend. But why are employers so quick to embrace this approach?

In addition to lower equipment costs for companies, BYOD means that employees can spend less time training to use new systems and harness the increased productivity of more familiar devices. BYOD also involves less accountability for managing IT assets, which workers can take to and from home at will. But for all of the conveniences and seeming efficiency, adding unmonitored devices that may have varying levels of security measures presents numerous opportunities for data breaches. 

Growing Mobile Use Statistics

Mobile devices are more ubiquitous than ever before for both professional and personal use. According to Statista, more than 91% of the global population (7.26 billion people) owns a mobile phone. The agency also found that 83.4% of people own a smartphone. This is a considerable rise, up from just 49.4% in 2016. 

Now that the overwhelming majority of the world owns smartphones, people commonly use them for tasks that were previously relegated to desktops and laptops. An August 2022 study found that 41.6% of emails were opened on mobile, with desktop browser email accounting for only 16.2% of opened emails. With so much of our information being stored and exchanged on mobile devices, understanding the potential data risks is essential. 

Misconception: Mobile Operating Systems Are Less Vulnerable 

Contrary to what consumers may assume, mobile devices are no more secure than other computers. Recently, the United States Computer Emergency Readiness Team (US-CERT) issued a report highlighting the dangers present in mobile devices. The report cited the increase in threats specific to mobile phones and existing vulnerabilities in all operating systems. This report also points out that typical attacks leverage mobile devices’ portability and their similarities to PCs. The mistaken perception that mobile operating systems are fundamentally more protected is dangerous, allowing hackers to take advantage of users’ naivete to exploit holes in their device security.

The Rise in Attacks Targeting Mobile Platforms and Devices

Mobile devices have many unique features, some of which introduce unique vulnerabilities. As global smartphone users increase, so do cybersecurity dangers. Recent years have seen a number of growing threats to mobile users. Among these, one of the most prevalent threats is mobile app fraud. A prominent breach in 2020 saw hackers use a massive network of devices to drain millions of dollars from online bank accounts, and single emulators can spoof thousands of devices simultaneously. Cross-border fraud is another rising concern, with 60% of businesses in the US and UK reporting incidents of this fraud type in 2021. 

Account takeover (ATO) attacks present yet another serious data security threat. Countless data breaches have leaked user identity information over time, making it easy for malicious actors to steal credentials that open doors to sensitive information. ATO attacks are one of the fastest-rising threats currently facing organizations and consumers alike. 2021 saw a nearly 20% increase in data breaches compared to 2020. Combined with phishing, social engineering scams, and AI-assisted machine-learning hacks, compromised login credentials are creating deep concerns among data security experts. 

The Need for Truly Secure Data

Known threats are not the only danger. According to the Identity Theft Resource Center’s 2022 H1 report, approximately 40% of data breach notices issued in the first half of 2022 did not include the root cause of the compromise. The top cause of data breaches so far this year is “unknown” due to a lack of missing root cause identifiers. For the first time since the ITRC began tracking data breach causes, the majority are unknown. Patching all of the potential holes in a security perimeter is especially challenging when not all threats are easily identified. The only truly safe solution is data that protects itself at every stage and, crucially, when accessed through any gateway.

BYOD policies are opening your network to a multitude of devices, many of which you cannot track or control. And while basic security measures like employee training, firewalls, and multi-factor authentication are still essential, they lose their value as soon as a breach has occurred. That’s why it’s vital to partner these measures with self-governing data, which protects against perimeter breaches. 

Traditionally, organizational data has been hidden behind firewalls and is left vulnerable to those already inside the system. However, 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.

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.

Instead of focusing on your network’s inherent shortcomings, we enable our partners to safely and confidently embrace the potential of a new online-oriented world. Data breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be.