How AI is Strengthening National Cyber Defense Strategies? 

Artificial Intelligence (AI) is rapidly reshaping global cybersecurity. For governments, defense organizations, and critical services, AI isn’t just a technology advantage, it’s becoming a national security necessity. From automating threat protection and insider risk analysis to enabling secure data sharing across networks and classifications, AI is transforming how nations defend themselves. However, while AI strengthens cyber resilience, it also introduces new risks that must be understood, verified, and secured.  

In this article, Tim Freestone, Director of Sales Engineering at Everfox, explores how AI is both a powerful tool for defense and a potential target, and how trusted, Cross Domain Solutions (CDS) can enable the safe and effective use of AI in the most sensitive environments.  

Governments and Critical Industries Have Become Priority Cyber Targets 

From the tactical edge to the enterprise cloud, the threat surface is expanding, and the stakes have never been higher. AI is now a crucial ally in building stronger national cyber defense strategies, but it’s integration also brings new risks that must be identified and managed.  

Artificial Intelligence for Cyber: Turning Automation into Advantage 

The amount of data being shared and collected across defense, government and Critical Infrastructure (CI) has grown exponentially, far beyond what human analysts can handle. AI is now transforming how organizations defend themselves by automating threat detection, prioritization, and response at unprecedented scale.  

Inside the Security Operations Centre (SOC) 

In the SOC, AI is relieving analysts from manual triage and log analysis.  By learning from patterns of malicious activity, AI can prioritize alerts, highlight abnormal behavior, and surface the most urgent threats faster. This not only saves valuable time but also enables human experts to focus on the incidents that matter most.  

Understanding Insider Risk  

AI is also strengthening insider threat programs by distinguishing between “normal” and potentially harmful behaviors. Trained models can correlate activity patterns, from data access to communication trends, to flag risks early. Reducing the chance of malicious or accidental data leakage before it impacts operations.  

Securing the Supply Chain 

In the software supply chain, AI-driven analysis helps identify vulnerabilities early in development. Automated code review and design scanning tools, powered by machine learning, are helping government and industry validate the security of systems before deployment.  

Protecting Classified Data 

For government and defense environments handling classified data, AI can assist in releasability decisions. Automatically summarizing or classifying content and helping reviewers determine what information can safely leave secure networks. In these high-stakes environments, even small data leaks can have outsized consequences.  

Learn more in 60 seconds: Cross Domain Solutions & Hardsec Explained | Securing Classified Networks (opens a new window) 

Defending Against Malicious Content 

AI models are being trained to detect phishing, malware, and manipulated media by analyzing vast amounts of digital content. Yet, adversaries are also using AI to evade detection. This ongoing “cat and mouse” dynamic makes it vital to verify and validate data before it enters sensitives systems. Ideally through hardware-verified or Cross Domain data transfer controls that help to ensure malicious content is filtered out at the source.  

In the United Kingdom (UK), the National Cyber Security Centre’s (NCSC) Active Cyber Defence (ACD) Programme is strengthening national resilience through AI-enabled capabilities including: 

• Enhanced threat detection 
• Automated takedown of malicious sites 
• Predictive analysis to anticipate attacks 
• Vulnerability discovery in critical software 

In the United States (U.S.), similar initiatives are being driven under the Cybersecurity and Infrastructure Security Agency (CISA) and the Department of Defense (DoD). CISA’s Joint Cyber Defense Collaboration (JCDC) is focused on integrating AI-driven insights into real-time national defense operations, improving: 

• Incident detection 
• Response coordination 
• Cyber threat intelligence sharing between government and private industry 

Meanwhile, the DoD’s Chief Digital and Artificial Intelligence Office (CDAO) is leading efforts to integrate AI into defensive and operational missions across all domains, ensuring that decision advantage, speed, and data integrity remain core to national cyber readiness.  

Together, these programs demonstrate a shared approach across allied nations: leveraging AI for faster detection, coordinated response, and the defense of CI, all while maintaining secure and trusted technology.  

“In critical environments, AI can’t operate in isolation, it must be trusted, verified, and secured from the ground up.”  - Tim Freestone, CYBERFORCE Summit 2025, hosted by Cyberani by Aramco Digital 

Cyber for Artificial Intelligence: Securing the Systems that Secure Us

While AI is transforming cyber defense, as we know, it also introduces new attack surfaces and dependencies that must be defended. As governments race to integrate AI into mission systems, the focus must shift from AI innovation alone to AI assurance, ensuring the systems themselves are secure, transparent, and resilient.  

The UK’s AI Cyber Security Code of Practice (2023)(3) provides clear guidance on building and deploying AI safely, including principles such as:  

• Creating segregated, secure environments for model development and testing 
• Sanitising training data to prevent model poisoning and bias 
• Securing APIs and data access layers to prevent exploitation 

In the U.S., this guidance is reinforced by: 

• The Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence (2023)(4), which mandates that federal agencies assess AI risks and implement strong security standards before operational use.  
• The NIST AI Risk Management Framework (RMF)(5), which outlines best practices for managing AI risks related to privacy, data integrity, and model security.  

These frameworks converge on a shared goal: ensuring that AI systems used in sensitive or classified networks are trustworthy, verified, and safe.  

This means:  

• AI models entering secure environments must be validated to ensure they contain no hidden or malicious code.  
• AI prompts and responses within classified systems must be controlled to avoid data leakage or model exploitation.  
• Data leaving sensitive environments must be verified, ideally through Cross Domain or hardware-based validation, to confirm it is releasable and uncompromised. 

The critical point however is, the defense of AI cannot rely on AI alone. Robust cyber hygiene, hardware-level verification, and trusted data pathways remain essential. Simplifying and verifying data through secure, logic-based transfer controls, such as Cross Domain Solutions that aim to provide assurance that only clean, authorized, and mission-relevant data flows where it’s needed.  

This is where Everfox operates, specialising in enabling secure, scalable AI adoption within the most sensitive government and defense environments. By creating segregated, trusted boundaries for AI interaction, Everfox helps national security organizations leverage AI’s capabilities, safely, compliantly, and at mission speed.  

Connecting AI and Cyber Readiness  

AI is redefining how nations defend themselves, but innovation alone isn’t enough. AI for cyber enhances detection, speed, and resilience. Cyber for AI ensures the technology itself remains trustworthy. The future of secure operations lies at their intersections, where AI innovation meets trusted connectivity.  

That’s where Everfox leads the way, securing the systems that secure national security.  

Everfox

At Everfox, we help governments, defense agencies, and critical industries in the U.S., UK, and across allied nations securely adopt AI and automation without compromising trust, sovereignty, or data integrity.  

Our Cross Domain Solutions provide the foundation for secure data access, transfer, and collaboration across multiple networks and classification levels. Empowering AI to work effectively where outcomes matter most.  

We connect the unconnectable, enabling mission-critical data to move securely from sensor to decision-maker to effector, powering the next generation of secure, AI-enabled defense.  

Sources

1. NCSC: Active Cyber Defence  (opens a new window)

2. UK Cyber Growth Action Plan 2025 (opens a new window)

3. AI Cyber Security Code of Practice (UK Government) (opens a new window)

4. Executive Order on Safe, Secure, and Trustworthy AI (U.S.) (opens a new window)

5. NIST AI Risk Management Framework (2023) (opens a new window)

Frequently Asked Questions:  

1. 1. How is AI being used to strengthen nation cyber defense? 
2. AI is helping governments and defense organizations detect, predict, and respond to threats faster than ever before. From automating SOC operations and insider risk detection to improving vulnerability management and data classification, AI enables defense teams to act at mission speed. Programs such as CISA’s Joint Defense Collaborative (JCDC) in the U.S. and the NCSC’s Active Cyber Defence (ACD) in the UK are already integrating AI to enhance national cyber resilience.  
3. 2, What are the main risks of using AI in sensitive or classified networks?  
4. AI introduces new attack surfaces, such as data poisoning, model tampering, or prompt exploitation, that can compromise data integrity or leak classified information. In national security environments, these risks are amplified by the sensitivity of the data AI interacts with. Secure deployment requires segregated AI environments, strict data validation, and trusted Cross Domain boundaries to help ensure models and their outputs remain safe and controlled.  
5. 3. How can organizations secure AI systems across multiple networks and domains? 
6. The key is to build trusted pathways for AI data. This means verifying all data entering or leaving AI systems, enforcing Zero Trust principles, and isolating AI workloads by classification level. Everfox Cross Domain Solutions (CDS) help to enable secure, scalable data access and transfer across domains. Meaning AI can operate effectively without compromising network security and mission readiness.  
7. 4. Why is securing AI important for the future of national defense? 
8. Because every mission now depends on data, and increasingly, that data is being processed and analyzed by AI. If AI systems are compromised, so are the missions that rely on them. Securing AI means securing the decision chain itself: trusting that the right data reaches the right person, at the right time, safely. Everfox enables that trust, connecting the unconnectable, at mission speed.  

Tim Freestone

Director, Sales Engineering

Tim is a Cross Domain Solutions subject matter expert and has helped to design and deliver government and defence systems worldwide. Tim’s current role is Director of Sales Engineering for Everfox where he manages teams of Sales Engineers and Architects. Tim provides input into the product strategy to ensure the products being delivered by meet any immediate and more general strategic customer needs.

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