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The AI Arms Race Shaping Federal Cyber Resilience

By Gary Barlet, Federal Chief Technology Officer, Illumio

At its core, the paradox of artificial intelligence (AI) in cybersecurity lies in conflicting uses. On one hand, malicious actors harness AI to launch sophisticated cyberattacks, exploiting vulnerabilities and evading traditional defense mechanisms with alarming efficiency.

Conversely, AI emerges as a powerful ally for defenders, offering advanced analytics and automation capabilities to bolster cyber resilience. AI-driven tools streamline operations by automating routine tasks and facilitating rapid threat detection and response, thus bolstering an agency’s ability to mitigate risks effectively. AI can also play a crucial role in securing hybrid environments by dynamically adapting security measures to the complex nature of such infrastructures, ensuring comprehensive protection across on-premises and cloud-based systems.

Machine learning (ML) algorithms, a cornerstone of AI, stand at the vanguard of this defensive revolution. Capable of analyzing vast datasets in real-time, they pinpoint anomalous patterns indicative of potential threats, empowering security teams with timely insights and recommendations.

AI as the Ultimate Defense to Outmaneuver Adversaries

In the ongoing cyber arms race, AI is beginning to emerge as a defense tool to help combat adversaries. By analyzing vast data sets and identifying patterns indicative of potential threats in real-time, AI empowers agencies to proactively detect and neutralize cyber threats before they can inflict harm.

For instance, as a new application comes online, AI can help recognize and auto-label the application. AI might identify it as a customer service application, an internal tool, or a third-party service, depending on the characteristics. Auto-labeling can help write basic rules that would typically require manual intervention to classify the application, segment it within the network, and establish appropriate security rules.

AI’s ability to analyze and process information at scale gives defenders a strategic edge, enabling them to anticipate and mitigate emerging threats more effectively than reactive security measures alone. Leveraging predictive analytics and behavioral modeling, agencies can discern subtle indicators of malicious activity and preemptively intervene to thwart attacks before they escalate.

Furthermore, AI-driven threat intelligence platforms empower agencies to aggregate and analyze data from diverse sources, yielding valuable insights into emerging cyber threats and adversary tactics. This comprehensive understanding of the threat landscape enables defenders to adapt their security strategies proactively, closing gaps and fortifying defenses against evolving threats.

The Power of AI and ZTS Working in Tandem

Through rule writing, auto-labeling, and other functions, AI/ML – paired with Zero Trust Segmentation (ZTS), also known as microsegmentation – can quickly and accurately create barriers and compartmentalize networks governed by rigorous authentication protocols. The integration of AL/ML plays a crucial role in Zero Trust frameworks, as these technologies enable continuous monitoring, anomaly detection, and adaptive access controls. Together, they enhance the effectiveness of the Zero Trust model in identifying and mitigating potential security threats in real-time.

ZTS is a foundational capability of Zero Trust that constantly verifies users through the visualization of all communication patterns and traffic between workflows, devices, and internet – allowing agencies to easily see and contain threats in the cloud, data center, network, and endpoints. ZTS protects against any potential threats, unknown actors, or unusual behaviors, so if an attack does occur, the actor cannot easily move throughout the environment and will be prevented from doing further damage.

Today, the convergence of AI and ZTS marks a critical juncture in defense strategies. AI augments ZTS by supporting real-time threat detection capabilities, automating policy enforcement, and enabling adaptive access controls. This symbiotic relationship empowers agencies to confront and neutralize evolving cyber threats, safeguarding critical assets with unprecedented agility and efficacy.

In the increasingly complex landscape of cyber threats, the integration of AI with ZTS also offers a formidable defense strategy. AI can continuously monitor network activities, user behaviors, and system configurations to detect anomalies or suspicious activities in real-time. Meanwhile, ZTS ensures that even authenticated users are subject to ongoing scrutiny, minimizing the risk of insider threats or unauthorized access.

Powered by ML algorithms, AI undertakes the monumental task of sifting through immense volumes of data in real-time, discerning subtle anomalies that may signify potential security breaches within segmented environments.  AI can identify unusual behaviors of a system’s peers (who they are talking to) and evaluations of exactly what is happening at the application level (what they are saying). AI solutions are ideally suited for this kind of problem that has multidimensional input and requires multi-dimensional output values that make up system identity.

AI assumes a pivotal role in ZTS frameworks by automating policy enforcement and fostering adaptive access controls. Through continual monitoring and analysis of network traffic, user behavior, and device attributes, AI-driven solutions exhibit a dynamic prowess, capable of adjusting access privileges in response to evolving risk factors.

This seamless integration of AI with ZTS not only enhances the agility and efficacy of cyber defenses but also underscores a proactive stance against emerging threats in today’s ever-evolving digital landscape.

The fusion of AI and ZTS presents an effective strategy for reinforcing cyber defenses amidst the ever-changing threat landscape. By integrating AI’s sophisticated threat detection capabilities and its capacity to automate policy enforcement, agencies can fortify the foundational principles of ZTS and enhance cyber resilience.

As agencies grapple with the complexities of the cyber realm, harnessing AI as the ultimate defense tool empowers them to not only thwart adversaries, but also to maintain a strategic advantage in the ongoing cyber arms race. Despite the evolving landscape of cyber threats driven by emerging technologies utilized by attackers, agencies can harness these very technologies to fortify their resilience and security posture, enabling them to adeptly navigate this dynamic and relentless realm of cybersecurity.

About the Author

The AI Arms Race Shaping Federal Cyber ResilienceGary Barlet is the Federal Chief Technology Officer at Illumio, where he is responsible for working with government agencies, contractors and the broader ecosystem to build in Zero Trust Segmentation as a strategic component of the government Zero Trust architecture. Previously, Gary served as the Chief Information Officer (CIO) for the Office of the Inspector General, United States Postal Service. He has held key positions on several CIO staffs, including the Chief of Ground Networks for the Air Force CIO and Chief of Networks for the Air National Guard CIO, where he was responsible for information technology policy and providing technical expertise to senior leadership. He is a retired Lieutenant Colonel from the United States Air Force, where he served as a Cyberspace Operations Officer for 20 years. Gary can be reached online at and at our company website

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