Category: Insights
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.
Protecting Critical Infrastructure from Cyberattacks
The last few years have seen a rise in the sophistication and frequency of attacks targeting many vital industries. In addition to the rise of international tensions bringing to light new threats aimed at critical infrastructure, advancing technologies have opened new doors for attackers. The increasing capabilities of artificial intelligence-enabled threats have been a popular topic of discussion, but many other vectors of attack pose equally dangerous threats to public safety.
Another major driver of new cyber threats came with the discovery of a modular malware toolkit capable of targeting tens of thousands of industrial control systems (ICS) across different industry verticals. These attacks pose a serious threat to critical infrastructure, such as power grids, water treatment facilities, and manufacturing plants, many of which rely on ICS to operate.
Some of the most potentially devastating and escalating new cybersecurity dangers have been aimed at critical infrastructure systems and public works worldwide. For example, in April 2023, Iranian state-linked hackers targeted critical infrastructure in the US and other countries in a series of novel dropper malware attacks. While not as devastating as other incidents, the previously-unheard of nature of the malware made this attack particularly concerning.
Other attacks on other areas of critical infrastructure in recent years have raised similar fears. In late 2022, the Danish State Railways’ network was temporarily shut down by hackers. Other breaches affecting essential industries continue to be reported frequently, with a ransomware attack affecting manufacturing, communications, public and private healthcare, and education being reported by the Cybersecurity & Infrastructure Security Agency (CISA) as recently as March 2023.
Attacks targeting public infrastructure that have the potential to take out essential systems — such as hospitals, water facilities, electricity, and energy production — are even sometimes referred to as “killware” for their ability to cause disruption leading to real-life deaths.
ICS and Critical Infrastructure
One reason for the increase in these attacks is the growing interconnectedness of ICS with other systems and networks. While this allows systems to benefit from the “network effect” and introduce new functionality, it also introduces new potential entry points for hackers to exploit.
Similarly, the rise of the Industrial Internet of Things (IIoT) has led to an increase in the number of devices and sensors connected to ICS, making it more difficult to secure the systems.
Industrial control systems are designed to control and monitor a wide range of physical devices and processes. This can include things like valves, motors, and sensors to ensure that they operate efficiently and safely.
Programmable logic controllers, distributed control systems, and supervisory control and data acquisition systems are all also enabled by the use of ICS. These devices and systems can be distributed across multiple locations and may be connected to other networks, such as corporate networks or the Internet.
Because of their integral role in managing physical processes, securing ICS and IIoT environments is essential to ensure the safe and efficient operation of critical industrial systems. But securing these environments can be challenging due to their inherent complexity, as well as the widespread use of outdated legacy systems and proprietary protocols. As a result, specialized security tools and techniques are required to protect ICS in IIoT environments from cyberattacks and other security threats.
Cyber Threats to Critical Infrastructure
While the number of potential attack vectors is virtually endless in today’s complex, interconnected systems, there are a number of particularly concerning threats to critical infrastructure that have emerged.
Advanced persistent threats (APTs) are a type of cyberattack specifically designed to target and compromise IIoT environments. APTs are typically carried out by highly skilled and organized threat actors using sophisticated and stealthy techniques to gain unauthorized access to vital systems and remain undetected for extended periods of time.
APTs targeting ICS in IIoT environments typically involve multiple stages. Hackers begin by conducting extensive reconnaissance to identify vulnerabilities and weaknesses in the target environment. They may use various techniques — such as social engineering, spear-phishing, and network scanning — to gather information about the target organization.
Attackers are adept at identifying openings, and unpatched software vulnerabilities, stolen credentials, and compromised third-party suppliers are all potential open doors. Once inside, attackers are free to unleash zero-day exploits, custom-designed malware, or other malicious programs to gain control of the connected systems.
Addressing APT and Other Cyberattacks
APTs and other common forms of attack can exploit a wide variety of openings to access a system, including using legitimate credentials. As such, they are particularly devastating when turned on systems that rely on conventional perimeter security. Once they get past the firewall or other perimeter security measures, they essentially have free rein to steal data or cripple internal systems.
This does not mean that vulnerable critical infrastructure cannot be protected, however. Self-protecting data can be an effective defense against APT attacks targeting IIoT environments by providing an additional layer of protection that directly addresses the greatest weaknesses in traditional network security.
Self-protecting data works by using encryption, access controls, and other security measures to protect data throughout its lifecycle, from creation to disposal. In a Zero-Trust system, files themselves are coded with the ability to recognize malicious activity and counter it immediately, regardless of who performed the action.
This means that even if an attacker gains access to the data, they will be unable to read or modify it without the appropriate decryption keys or credentials. Likewise, approved users are blocked from accessing or performing harmful actions, whether on purpose or by accident.
Zero-Trust Security in Infrastructure IIoT Applications
In an IIoT environment, self-protecting data can be used to protect sensitive information, such as configuration data, operational data, and customer data. For example, self-protecting data can be used to encrypt configuration files for ICS devices, making it more difficult for an attacker to modify the settings of these devices. Similarly, self-protecting data can be used to encrypt customer data, such as personally identifiable information (PII) or financial information, making it more difficult for an attacker to steal.
Additionally, self-protecting data can help organizations detect and respond to APT attacks by providing visibility into how data is being accessed and used within critical ICS. By monitoring access logs and other data-related activities, security teams can detect suspicious behavior and take appropriate action to mitigate the threat.
Sertainty
Sertainty’s foray into the Transient World is manifested in multiple Bi-National Research and Development (BIRD) Proposals\Submissions. These innovative solutions have the potential to aid government agencies such as Homeland Security as well as companies in the transportation and energy industries.
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. Security breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be.
What Is the CISA Zero Trust Maturity Model?
In recent months, the federal government has renewed its focus on digital security. The Cybersecurity and Infrastructure Security Agency (CISA) has been applying pressure on both the private and public sectors to increase commitment to digital security and Secure-by-Design Technology.
While there is an eminent need for improved security protocols across the board, the technology to fill these needs in both government and civilian applications has already been successfully introduced in many industries. Rather than reinventing the wheel, the CISA Zero-Trust Maturity Model prompts federal agencies to introduce these tools to mitigate the weaknesses noted.
The Need for Increased Cybersecurity
The world of cybersecurity is evolving rapidly. Yet, despite the constant emergence of new threat vectors, data protection in many critical areas is fundamentally lacking. From major social media platforms to federal agencies, conventional perimeter security remains the de rigueur.
While perimeter security will always be an essential element of a comprehensive data security plan, even the most sophisticated perimeter systems are vulnerable to attackers that have found ways to breach the layers of exterior security. Likewise, insider threats often go unmitigated by perimeter-based security measures, as malicious actors may already have legitimate access credentials.
These weaknesses mean that securing data behind firewalls and “secure” servers is essentially an arms race between network administrators and people attempting to break in. This is particularly problematic when the systems in use have been around for an extended period of time, such as in the relatively outdated systems that many government agencies continue to use.
In recent months, these threat vectors have been highlighted by increasing AI-enabled threats. Even mainstream artificial intelligence programs can be used to exploit weaknesses in security perimeters. For example, hackers have already begun using programs such as ChatGPT to generate more effective social engineering attacks, exacerbating the extant threat to validated user credentials.
Addressing Weaknesses in Conventional Data Security
In spite of the vital nature of private data in government hands, many federal agencies continue to rely on outdated legacy systems to collect, store, and access their information. The implicit trust built into these systems is based on perimeter security protocols, where access and authorization are infrequently assessed based on fixed attributes.
To address the above (and other) weaknesses, a full rethink of how to secure data is required. Fortunately for the vulnerabilities plaguing many critical sectors, an entirely new generation of cybersecurity does exist: 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 a Data-File or Datasets, Sertainty leverages patented processes to govern, track, and defend data by the data itself.
Instead of the file’s security being based on granted privileges to access the network directory where the file currently resides, Sertainry Self-Protecting Data files protect themselves against malicious activity immediately. With these protocols, the data remains secure even when systems are compromised.
Prompted by the now-exposed cybersecurity realities, regulators recognized the shortcomings inherent to the state-of-the-art cybersecurity protocols. A 2021 Executive Order titled “Improving The Nation’s Cybersecurity” outlined the need for US federal agencies to move on to something better – a Zero-Trust Architecture.
Executive Order 14028 and the CISA Zero Trust Maturity Model
In April 2023, CISA published what is known as the Zero Trust Maturity Model (ZTMM). This security model is designed to overcome many of the inherent assumptions built into modern networks, contributing to their cybersecurity weaknesses.
This new focus is not simply a function of natural evolution but an answer to federal demands for better security. Executive Order 14028, “Improving the Nation’s Cybersecurity,” requires all federal agencies to develop a plan to implement a Zero-Trust Architecture to address real shortcomings in current sensitive data storage.
Already, some agencies have been proactive in introducing a Zero Trust concept. In 2021, Representative Dr. Mark Green (R-TN) of the House Committee on Armed Services successfully incorporated the Sertainty language regarding data security into the Department of Defense 2020 DoD Strategy. Rather than calling for generic security measures, the language of the DoD Strategy favors the functionality that Sertainty technology can offer.
Private Sector Application of the Zero Trust Maturity Model
Regarding growing threats to data security, the private sector has not escaped direct scrutiny, either. This year, CISA director Jen Easterly criticized tech companies for their failure to prioritize the safety and privacy of consumers. While Director Easterly’s criticism was aimed primarily at technology companies, organizations in all industries are in need of enhanced data security.
While the CISA ZTMM model was specifically developed for federal agencies, many in the private sector took notice. The model provides an approach for any organization to achieve continued modernization efforts related to zero trust — which is crucial in a rapidly evolving technology landscape.
This need for Secure-By-Design technology goes hand-in-hand with the ability to create files with self-protecting abilities. Tools such as the Sertainty Data Privacy Platform allow developers to utilize cutting-edge methods and protocols in their applications from the outset, as well as apply them to existing systems.
Sertainty Data Privacy
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. Cyber threats may continue to advance, and security perimeter breaches may be inevitable, but with Sertainty, privacy loss doesn’t have to be.
Could Zero Trust Security Have Prevented the Recent Pentagon Breach?
While data security breaches are a common occurrence, some attract more attention than others. Earlier this year, the US Special Operations Command (USSOCOM) confirmed that hundreds of sensitive Department of Defense documents were leaked over a period of two weeks.
The Senate defense appropriations subcommittee demanded answers for how a single individual could have taken and distributed classified information without being detected, in which top security experts were quick to note that insider attacks such as this one are prevalent.
Insider attacks have been a primary motive behind many ongoing efforts to increase federal data security, including a shift to Zero Trust methods. In fact, the US Navy Chief Technology Officer Dan Yeske said in a recent interview that, had the Pentagon already adopted a Zero Trust data security model, the military would have recognized and responded to breaches like this one sooner.
The Current State of Federal Data Security
When considering security for sensitive data, the common perception may be that confidential military or government data is fundamentally more protected than information stored by private companies. However, the reality is that many of the same threats apply to both.
This is why the Zero Trust paradigm has been gaining attention and traction across industries, including the governmental sector. As it stands, the Pentagon already has a plan in place to introduce a Zero Trust security model into effect, by 2027.
This plan by the US government aims to shore up other cybersecurity efforts for all federal agencies. In April 2023, the Cybersecurity and Infrastructure Security Agency (CISA) published what is known as the Zero Trust Maturity Model (ZTMM) in response to an Executive Order (14028) calling for “Improving the Nation’s Cybersecurity.” Order 14028 requires all federal agencies to develop a plan to implement a Zero Trust architecture to address the shortcomings in the current data protection constructs.
It should be noted, that the Zero Trust Framework has already been successfully introduced in many industries. Rather than reinventing the wheel, the US Government has mandated Federal Agencies to adopt the CISA Zero-Trust Maturity Model into existing tools to mitigate network weaknesses.
While the CISA ZTMM model was specifically developed for federal agencies, many in the private sector have also taken notice. The model provides an approach for any organization to achieve continued modernization efforts related to Zero Trust — which is a criticality within a rapidly evolving technology landscape.
The Role of Zero Trust in Securing Pentagon Data
The US Navy CTO – Yeske – has been stating very poignantly time and again that Zero Trust security could have empowered a faster and more effective response to breaches and Pentagon data leaks. While this highlights some of Zero-Trust’s key benefits thereof, there is a game-changing potential in utilizing Self-Protecting-Data that go beyond simple protection.
It is also important to note that in addition to the benefits mentioned by CTO Yeske, the true value of Self-Protecting-Data files is in preventing a rogue agent from accessing or sharing the files, to begin with. To fully realize the benefits of Self-Protecting- Data, agencies need to set their sights even higher than the military’s current plans.
While it is certainly true that a Zero Trust system would have allowed the Pentagon to recognize the breach far sooner than the six months that it took, properly implemented Zero Trust protocols could have stopped a rogue actor instantly when attempting to access unauthorized files.
This is true in the vast majority of information leaks, Zero Trust could have prevented many breaches in both the public and private sectors. As it stands, insider threats persist as the most ubiquitous threats to private data in all sectors. According to a 2022 report, insider threat incidents have been on an incline, and rose by 44% over the two previous years, with the cost per incident rising by an average of more than 30% year-over-year.
The perception that the primary benefit of adopting a Zero-Trust posture entails identifying and responding to leaks is rooted in a conventional understanding of information security. Traditional digital security is fundamentally reactive. This means that, in many cases, Zero Trust is used as an enhanced form of traditional data privacy systems, and remains dependent on networks and demarcations. While this is an improvement, effectuating the implementation of Self-Protecting-Data will atone for existing vulnerabilities within a Security Perimeter in which the data transverses and is consumed.
In all, perimeter security will always be an essential element of a comprehensive data security plan. Most sophisticated layered Perimeters are vulnerable to cyberattacks. Threats often go unmitigated, due to insiders with legitimate access credentials, as was the case in the most recent Pentagon breach.
Zero Trust seeks to address weaknesses in ensuring data privacy. A Zero-Trust-Architecture at the Data-Layer untethers reliance on security Perimeters and Identity Access Management systems, to enable data files to protect themselves independently through an embedded trust-cycle.
Truly Secure Data with Sertainty
Sertainty has redefined how information is protected to ensure data privacy even where firewalls fail. Using cutting-edge protocols and embedding intelligence directly into data files and datasets, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself. These protocols mean that the data remains secure even if systems are compromised.
At Sertainty, we know that data is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs.
As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing Self-Protecting Data solutions that evolve and grow to defend your crown jewels. Instead of focusing on your network’s inherent shortcomings, we enable you to safely and confidently embrace the potential of a new online-oriented world. Our self-protecting Zero Trust protocols mean that even if systems are compromised, data remains secure.
Addressing Primary Open-Source Security Challenges
In the modern era of computing and data storage, the most critical element of any system is the software on which it runs. While hardware is still important, devices have developed to the point where the differences between compromised and secure networks, databases, and files come down to code, not physical security measures.
One thing that has not changed since the earliest days of computing, however, is the rapid rate at which technology develops. Likewise, the importance of keeping up is a major factor for any business that hopes to stay relevant or secure. Due to this, as well as the high cost of proprietary software tools, open-source software (OSS) has come to dominate the world of coding.
What Is Open-Source Software?
In the world of software development, the term “open-source” refers to any software with accessible source code that anyone can modify and share freely. Protocols, algorithms, and even fully-developed programs and games can be created with open-source coding.
In most cases, open-source code is adapted and integrated into programs where it can be useful. Because source code is the part of the software that users don’t see or interact with, common open-source code is, at times, worked on by hundreds or even thousands of independent parties that can be used seamlessly without any outwardly-recognizable signs.
In the early days of computing, there were very few dedicated professional programmers, and so the early internet was almost entirely made up of open-source code. The efforts of enthusiasts and professionals alike were aided by the network effect as the internet grew in popularity, allowing more people to contribute and refine the very protocols that were connecting them.
Today, many companies employ in-house software engineers; however, much of the code that we still use relies on the efforts of open-source developers. In fact, a 2019 report by Gartner found that 96% of codebases contain at least some open-source code.
Advantages of Open-Source Software
There are many reasons why open-source coding is still so common. When compared to private development, open-source programs have many advantages. By giving programmers direct access to a program’s source code, the software can be continuously improved and expanded. This allows developers to add new features and fix bugs as they arise, rather than having to rely on the software’s original developer to address these concerns.
The ability to grow and adapt quickly is essential to success in today’s increasingly fast-paced work environment. Organizations attempting to stay on top (or simply keep up with the market) have needs that evolve rapidly. Because of this, many companies look for solutions with the least amount of friction between development and implementation.
Dangers of Open-Source Software
For all of the advantages that open-source software brings, there are a number of very significant risks stemming from the very aspects that make it so adaptable. And as prevalent as open-source coding is, a staggering number of organizations lack the structure to address these risks. A 2022 report by the Linux Foundation found that less than half of businesses had an open-source security policy in place for OSS development or usage.
This lack of preparation can open the door to a wide variety of cyberattacks. Because anyone can access the source code of these programs, any flaws or vulnerabilities could quickly become public knowledge. Malicious actors can also freely examine the code that underlies any programs utilizing a piece of open-source software.
The exploitation of these vulnerabilities can have wide-ranging negative impacts on all sorts of businesses. Everything from proprietary business data to private medical records can be compromised by attacks utilizing loopholes in open-source code.
On a more sophisticated level, there are numerous ways in which open-source code can be compromised by hackers, causing anyone who then uses it to fall into their hands. For instance, if a code is compromised before it is used, any flaws built into it will remain there unless specifically eliminated. This may sound simple, but the reality is far more challenging. Unless security experts know precisely what to look for and where to look for it, detecting malicious lines of code can be virtually impossible. Even attempting to do so requires knowledge of whether the code has been compromised to begin with. In most cases, however, vulnerabilities do not become known until they have already been exploited.
Types of Open-Source Security Risks
To better understand how the aforementioned attacks can occur, let’s examine some of the most common methods that hackers use to inject malicious code into open-source programs.
Upstream Server Attacks
In upstream server attacks, malicious entities infect a system “upstream” as it is uploaded onto a computer system or device. To accomplish this, malicious code is added to the software at its source, often through a malicious update, infecting all users “downstream” as they download it.
Midstream Attacks
Midstream attacks are fundamentally similar to upstream attacks, but instead of tampering with code at its initial source, they target intermediary elements. These include software development tools and updates that pass on the malicious code from there.
CI/CD Infrastructure Attacks
Another variation of the upstream attack model, CI/CD infrastructure attacks introduce malware into the development automation infrastructure of an open-source code requiring “continuous integration” or “continuous delivery” steps.
Dependency Confusion Attacks
Unlike the previous three types of attacks, Dependency Confusion Attacks exploit private, internally-created software dependencies by registering a new dependency with the same name in a public repository with a higher version number. The malicious code is then optimally placed to be pulled into software builds in place of the latest legitimate version of the software.
Case Study: Log4Shell
Regardless of whether hackers compromise open-source code by one of the above methods or learn of a genuine loophole from an open hacking forum, once a door has been opened, any and all data within the compromised system is immediately vulnerable. Some measures can be taken to avoid some of these, but even the biggest companies have fallen prey.
One of the most dangerous and well-publicized instances of open-source software falling vulnerable to attack came in 2021 when a code-execution vulnerability exploit for Log4j was released. At the time, Log4j was a virtually ubiquitous open-source utility used in countless popular applications, including Microsoft, Amazon, and Twitter servers.
Referred to as “Log4Shell,” the vulnerability was first reported in November of that year after being identified in the popular game Minecraft. The code exploit was also published in a tweet a few weeks later, leading to numerous forums warning users that hackers could execute malicious code on servers or clients running the Java version of Minecraft.
Millions of servers were left vulnerable by the exploit. The Apache Software Foundation assigned Log4Shell the highest-possible severity rating in the Common Vulnerability Scoring System (CVSS), and the director of the US Cybersecurity and Infrastructure Security Agency (CISA) called the exploit a “critical” threat. Using Log4Shell, attackers were able to install blockchain crypto, steal system credentials, and access sensitive data before a patch was released.
Truly Secure Data with Sertainty
The simultaneously derivative and interconnected nature of the modern internet makes avoiding open-source code a practical impossibility. For this and other reasons, traditional perimeter security falls notably short when it comes to keeping malicious actors out of your system.
Because of this omnipresent threat, 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 or accessed from the inside, all data stored in them 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 future-proof approach to 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.
Understanding Self-Protecting Data Governance
In the modern era, data governance plays a greater role than ever before. Businesses across industries, infrastructure, and government services all rely on a constant stream of accurate, up-to-date information to function.
With each passing year, both the volume and depth of information being gathered and stored grow exponentially, increasing the need for top-notch data governance in turn. While the levels of automation and capability available today far surpass past data management options, when it comes to securing that data, many organizations still operate in the “dark ages” of cybersecurity.
What Is Data Governance?
According to the Data Governance Institute, data governance is a “system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.”
Put more simply, data governance refers to any actions that your organization takes to input, track, share, secure, and dispose of the information you gather. Sometimes, all data governance functions are handled by a single, comprehensive system. There are certain advantages to the simplicity of a single, unified platform, but more sensitive data often requires a more specialized approach.
Regardless of whether all data within a system is taken in, stored, shared, and accessed within a single platform, security is one notorious pain point in many data governance systems.
Why Does Secure Data Governance Matter?
Some organizations simply rely on network firewalls and secure access protocols to keep their information secure, but these measures are often woefully inadequate. When dealing with any information, whether it be for a small private business or a high-level government intelligence agency, proper data protection is absolutely essential.
Overall, good information security is valuable for innumerable reasons. That said, from a data governance perspective, there are two primary concerns stemming from infosec: accuracy and privacy.
For one, if the data collected and stored within a system is to be of any use, it needs to be precisely and verifiably accurate. If files can’t be tracked at every step, with only approved users making verified changes to them, attempting to rely on the information therein carries significant risk. The fallout from making decisions based on faulty data can range from moderately damaging to catastrophic, depending on the source and nature of the inaccuracy.
Of equal concern to many organizations are the regulations surrounding the data they collect and handle. HIPAA, CCPA, GDPR, and many other forms of legislation both in the United States and abroad enforce the need for secure data files with steep consequences.
Following a number of high-profile data breaches, the maximum fines for noncompliance in many of these areas are increasing. In some cases, criminal charges may even be laid if a company is determined by the court to have been negligent in its secure data governance policies. In some instances, security noncompliance can even lead to issues of national security.
As such, any data governance strategy needs to include a comprehensive security plan. Even within an ostensibly secure network, if users within a system have unfettered access to data stores, the files therein are susceptible to tampering. This is where self-protecting data and Zero-Trust protocols enter the picture.
The Role of Self-Protecting Files in Data Governance
As we mentioned above, when it comes to securing sensitive information, many organizations — even those handling potentially volatile private data — often still rely on fundamentally outdated types of perimeter security.
Traditionally, the focus of digital privacy systems has been to keep outsiders from accessing the private networks and stores where data is hosted. While there will always be a place for maintaining this security perimeter, relying on this alone leaves all data within vulnerable to anyone who has already gained access to the servers or data files. Although new upgrades are constantly being made to firewalls and user authentication systems, attempting to truly protect data with this type of security framework is a perpetual game of catch-up.
This is where a Zero-Trust framework for self-protecting data can be of the most use. Rather than simply trying to improve on perimeter measures, self-protecting data reimagines the entire approach to security. As the name implies, the goal of self-protecting data is not just to keep hackers out of your system but to create truly secure files. Instead of being left accessible to any “trusted” users, self-protecting files themselves are coded with the ability to recognize malicious activity and counter it immediately, regardless of who appears to be performing the action.
Because these systems operate on a Zero-Trust basis, basic perimeter security like password-protected logins becomes a first layer of defense rather than the sole source of protection for your files. This allows for data governance solutions that can be relied upon to be both accurate and secure.
Creating Secure Data Governance Solutions
While implementing a self-protecting data framework independently of other data governance tools is possible, built-in security is often a smoother, more elegant solution. For this reason, Sertainty UXP technology goes beyond simple “plug-and-play” security options. Sertainty is pioneering a new, innovative Self-Protecting Data Governance category to address the unique needs of data privacy programs.
Corporations and institutions facing data leakage, compliance issues, and Personal Identifiable Information (PII) theft can all benefit from unique, tailored solutions, and with the Sertainty Software Development Kit, novel information security programs can be created to not only meet but surpass other, less optimized data governance solutions.
Truly Secure Data Governance 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 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 evolve and grow to defend sensitive data. Threats to security may be inevitable, but with Sertainty, privacy loss doesn’t have to be.
Could Zero-Trust Security Prevent Famous Data Breaches?
Many security systems claim to be trustworthy, but when it comes to data security, few things are more important than real-world results. Ever-evolving claims of improved interfaces and threat detection software, “next-generation” systems, and many other promising developments, have been around for as long as we have been using computers. Yet, despite these claims, major data breaches occur all the time. Sophisticated infiltration methods match or exceed the pace of conventional security development, and social engineering and phishing scams are increasingly prevalent.
While looking to the future is crucial to creating better data privacy solutions, security experts begin by examining the past. New systems have to not only provide solutions for emerging problems but address historic threats with meaningful changes.
Types of Data Security
While there are many different methods and tools used to protect data, most of these measures are aimed at achieving one of two goals: keeping malicious actors out of private data systems, and ensuring that organizations are protected in the event of a breach.
The first and most common focus in data protection is to create a secure storage environment. Tools for securing databases can include physical hardware security, passwords, firewall, proxy servers, user authentication, and more. All of these together form what is commonly referred to as perimeter security. Data destruction and proper sanitization of old devices can also play a role in protecting the integrity of data centers.
While perimeter security is aimed at keeping criminals out, however, traditional digital security is more reactive and perpetuates the vulnerabilities. Data backups and other redundant systems do help a company recover information in the event of ransomware and other attacks. However, it is always preferable to prevent attacks in the first place. To blaze new trails in the creation of cutting-edge data privacy measures, such as Zero-Trust methodologies, are a must if we are to preempt cyberattacks.
Revisiting Recent Data Attacks
Perimeter security and data backups are standard measures, but neither provides a fully-integrated and comprehensive solution. This is evidenced by the fact that all of the organizations discussed below employed these methods and still suffered breaches.
Zero-Trust protocols, on the other hand, prevent hackers from gaining the power to steal any sensitive data, even if outsiders do find a way past corporate firewalls — or are based on the inside. To understand how much of a difference Zero-Trust can make, let’s examine some of the highest-profile data breaches of the last decade and assess whether or not Zero-Trust security could have prevented these attacks.
Yahoo
Over the course of two instances, Yahoo suffered the largest recorded data breach to date. Two attacks, one occurring in mid-2013 and the other in late 2014, were belatedly reported by the company in 2016. The breaches were accomplished using cookie-based attacks, which allowed hackers to enter the system as authenticated users. This attack has been largely attributed to “state-sponsored” agents (with many pointing fingers at the Russian government).
Overall, over 3 billion user accounts were affected by the breaches. The fallout from these attacks not only led to class action lawsuits but also reduced the acquisition price of the company by Verizon by $350 million.
SolarWinds
A more recent example of a high-profile breach occurred in 2020, when SolarWinds, a major US information technology firm, was the subject of a sophisticated cyberattack. Hackers broke into SolarWinds’ system and added malicious code that was later sent out as part of a routine update to clients of SolarWinds. Once installed, hackers were able to gain access to all manner of sensitive information in those customers’ own systems, including US government agencies like the Department of Homeland Security and the Pentagon.
Facebook/Meta
Meta is no stranger to large-scale data breach incidents. The most recent known attack on Facebook was revealed in 2021 when private data from 533 million user accounts appeared on a public internet forum. While the attack was dismissed by Meta as the result of Open-Source Intelligence (OSINT) scraping, it was later revealed that hackers had accessed the information by exploiting vulnerabilities in Facebook’s Contact Import feature. This followed a June 2020 incident where Facebook accidentally shared private user data with third-party developers.
Truly Secure Data with Zero-Trust
While each of these attacks was achieved using different methodologies, the common thread between them all (and most other data leaks) was in hackers finding a way to access private databases. This access could be the result of compromised user credentials, such as, in the case of Yahoo, code attacks on client transmission and patching (i.e., SolarWinds), system loopholes (Facebook), or even simple mistakes.
The findings suggest that regardless of which method is used to gain entry, the real damage is done once malicious parties are inside the security perimeter. Even if backups are used to prevent data destruction or ransom, the damage of leaked private information is irreversible.
Both, conceptually and in practice, Zero-Trust addresses data privacy’s greatest weaknesses. Rather than relying on security perimeters – with the assumption that users within a system have the right to access its information, Zero-Trust security enables data files to protect themselves through independent verification. In a Zero-Trust security framework, users are continuously verified and authenticated, ensuring that data remains secure even if the system is compromised.
Zero-Trust Security from Sertainty
With heightened information security threats, securing sensitive data in all sectors is more crucial than ever. Traditional perimeter security is becoming increasingly inadequate in the face of smarter, more motivated attacks.
Sertainty has redefined how information is protected to ensure data privacy even where firewalls fail. Using cutting-edge protocols and embedding intelligence directly into data files and datasets, Sertainty leverages proprietary processes that enable data to Govern, Track, and Defend itself. These protocols mean that the data remains secure even if systems are compromised.
At Sertainty, we know that data is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be Intelligent and Actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs.
As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing Self-Protecting Data solutions that evolve and grow to defend your crown jewels. Instead of focusing on your network’s inherent shortcomings, we enable you to safely and confidently embrace the potential of a new online-oriented world. Data breaches may be inevitable, but with Sertainty, privacy loss is moot.
The Implications of International Tensions on Cybersecurity
As international tensions rise around the globe, experts in all areas of security are taking a closer look at data protection. While cybersecurity threats are an ever-present risk, increasing international tensions have led to the emergence of various other threats, including transnational terrorism and the use of chemical and other unconventional weapons.
The ensuing chaos from the increase in international tensions opens the doors for opportunistic hackers and cybercriminals to wreak havoc in vulnerable regions worldwide. Even in areas not in direct conflict, instability has presented challenges in keeping government and organizational data safe in increasingly at-risk environments.
Rising Overseas and Domestic Threats
The war in Ukraine, Chinese incursions into Taiwan, continuing Iranian-US tensions, and various other emerging potential issues have opened doors for all cyberattacks.
As recently as December 2022, the Center for Strategic and International Studies identified potential spyware hacks of US government employees, including diplomats in multiple countries. In the previous month, the CSIS identified 12 different incidents where the US, Ukrainian, Polish, Bahraini, Pakistani, and numerous other governments were targeted by cybercriminals.
Although many of the attacks reported by the CSIS come directly from foreign entities, data breaches can come from anywhere, and accessing confidential, vulnerable information can impact a country’s operations or wreak havoc on critical infrastructure. The number of nation-state cyber attacks against critical infrastructure has doubled in the past 12 months.
In late 2022, the Danish State Railways’ network was temporarily shut down by hackers. However, in 2021, an even more powerful attack against the Colonial Pipeline cut off oil supplies to a large section of the eastern United States. While neither of these attacks appeared to be the work of hostile governments, as tensions rise, so does the potential for damage from similar breaches.
When it comes to threats against intelligence data gathered by government agencies, the dangers can sometimes be exponentially more dangerous. While direct attacks against critical assets have immediate, tangible consequences, the sensitive nature of national intelligence data means that breaches can have cascading effects. Not only do intelligence data breaches potentially endanger the lives of operatives currently in foreign countries, but the revelation that intelligence operations are ongoing can also justify more direct actions.
In some cases, information gathered and the methods by which it was acquired can have catastrophic effects on international relations. When tensions are already high, volatile data can be the final straw that dismantles international relations when compromised. Even friendly countries can find themselves at odds over foreign agencies’ methods of collecting data. Because of these factors, securing intelligence data takes on particular importance during times of rising international tensions, even if the countries in question are not directly in conflict with each other.
Another genuine factor that makes securing intelligence data particularly critical is the potential for harm from compromised internal sources. Whether an operative leaks data themselves or is unintentionally compromised, it can devastate national security or national trust. Examples of these security compromises include the WikiLeaks release of 2010 and the reveal of the PRISM program.
Challenges to the Private Sector
While the threats to government or infrastructure assets may be the most immediately apparent, data within the private sector can also see increased incidences of targeting during times of international tension or conflict. In addition to purely profit-motivated attacks like the Colonial Pipeline, governments may encourage hackers to after businesses in other countries. Hacking businesses internationally can be a strategic move to disrupt industry during wartime or destabilize other countries’ economies to their advantage.
Additionally, the increased attacks can compromise sensitive information between the public sector and private contractors, as demonstrated by major security breaches at General Dynamics, Boeing, and Raytheon in the United States in recent years. By exposing private and public security vulnerabilities, international adversaries can access anything from personal information to blueprints for thermonuclear warheads.
Responding to Threats with Truly Secure Data
With heightened global tensions, securing sensitive data in all sectors is more crucial than ever. Traditional “perimeter security,” which protects data by keeping outsiders from accessing a system, becomes increasingly inadequate in the face of motivated attacks.
In many cases mentioned above, compromised passwords and user information were to blame for breaches. Even when attacks take on more sophisticated forms of cyberattacks — such as the DDoS attacks against the Italian and Finnish governments and several major US airports in 2022 — attempting to secure sensitive information with traditional perimeter security is inadequate.
Both conceptually and in practice, Zero Trust addresses data privacy’s greatest weaknesses. Rather than relying on a series of firewalls and assuming that users within a system have the right to access information stored on the server, Zero Trust security enables data files to protect themselves through independent verification. Through a Zero Trust security framework, users are continuously verified and authenticated — ensuring that data remains secure even if the system is compromised.
Integrate a Zero Trust Architecture with Sertainty
Sertainty has redefined how information is protected to ensure data privacy even where firewalls fail. Using cutting-edge protocols and embedding intelligence directly into data files and datasets, Sertainty leverages proprietary processes that enable data to govern, track, and defend itself. These protocols mean that the data remains secure even if systems are compromised.
At Sertainty, we know that data is the most valuable asset to your organization’s continued success. Our industry-leading Data Privacy Platform has pioneered what it means for data to be intelligent and actionable, helping companies move forward with a proven and sustainable approach to their cybersecurity needs.
As the digital landscape evolves and networks become more widely accessible, Sertainty is committed to providing Self-Protecting Data solutions that evolve and grow to defend your crown jewels. Instead of focusing on your network’s inherent shortcomings, we enable you to safely and confidently embrace the potential of a new online-oriented world. Data breaches may be inevitable, but with Sertainty, privacy loss is moot.