Navy Integrates AI-Enhanced Zero Trust for Cyber Defense

Published Date : 8/7/2025 

The U.S. Navy is integrating AI into its zero trust framework to enhance identity and access management, ensuring robust cybersecurity in a rapidly evolving threat landscape. 

As the U.S. Navy confronts a rapidly evolving cyber threat landscape marked by increasingly sophisticated adversaries and the growing use of AI by both state and non-state actors, it is accelerating efforts to modernize its cybersecurity posture through the adoption of zero trust principles. In particular, the Navy is exploring how AI can support identity and access management by enabling continuous, context-aware authentication across its enterprise.

The Navy’s integration of AI into its zero-trust architecture reflects a broader pivot toward adaptive, behavior-informed cybersecurity that accounts for the complexity and dynamism of the modern threat environment. As digital battlespaces expand and adversaries embrace AI-enhanced tactics, the Navy is building a cybersecurity foundation that seems to be rooted in data, identity, and continual verification.

While many of these capabilities are still in development or early deployment, the Navy’s leadership in zero trust implementation, especially using platforms like Flank Speed, signals a long-term commitment to resilient, intelligence-driven defense across both enterprise and operational domains. In contrast to traditional perimeter-based defense models, zero trust assumes that no user or device, internal or external, should be inherently trusted. Instead, access decisions are dynamically evaluated based on real-time risk assessments. The Navy’s approach to zero trust aligns with guidance from the Department of Defense (DOD), the Office of the National Cyber Director, DOD’s 2022 Zero Trust Strategy and Roadmap, and Executive Order 14028.

At the core of this strategy is recognition that modern cyber threats demand modern defenses. Defenses that can evaluate not only who is requesting access, but whether the way they are doing so aligns with established behavioral patterns and mission context. The Navy has begun piloting AI models to analyze behavioral indicators as part of continuous identity verification. According to David Voelker, NAVWAR SYSCOM Standardization Officer also responsible for supporting cybersecurity and Zero Trust implementation across the Navy, AI is being used to assess user behavior over time by evaluating patterns in login locations, time-of-day access, device usage, and frequency of interaction with enterprise resources. These behavioral signals allow security systems to build dynamic user profiles and to detect anomalies in real time.

In a recent interview with Federal News Network, Voelker described this approach as a shift away from static mechanisms like passwords or common access cards. “If I have someone logging in at 8 AM every day from a known device, that’s very different from an access attempt at 2 PM from an unfamiliar endpoint,” he said. “We’re taking those kinds of environmental cues and incorporating them into a dynamic model for trust.” In this context, AI enables more granular risk scoring and anomaly detection. Rather than issuing binary access decisions, AI-supported systems can apply conditional access rules, prompt for additional verification, or alert cybersecurity personnel, all without overwhelming analysts with false positives.

The Navy’s enterprise Microsoft 365 cloud environment, known as Flank Speed, has become a proving ground for its zero trust efforts. As of 2024, Flank Speed had met 151 of the 152 technical requirements outlined in DOD’s Zero Trust Capability Execution Roadmap, placing the Navy well ahead of the department’s Fiscal Year 2027 compliance goal. According to the Navy, “Flank Speed is a permanent, single enterprise solution for daily work, offering a secure environment for collaboration, cloud storage for files and documents, and Microsoft Office 365 productivity tools.” The transition plan supports more than 750,000 users and is structured around infrastructure readiness and mission priorities.

Although specific details of AI integration with Flank Speed have not been publicly disclosed, the platform includes advanced security analytics capabilities that support continuous monitoring and policy enforcement at scale. Its architecture enables the Navy to test identity management and conditional access controls in a controlled, enterprise-wide environment. While Flank Speed addresses enterprise IT environments, Navy leaders are also working to bring zero trust principles into operational technology (OT) and weapons platforms. Navy Chief Information Security Officer Tony Plater has emphasized the need to secure all layers of the digital battlefield from cloud infrastructure to embedded shipboard systems.

According to DefenseScoop, the Navy is developing formal implementation standards to extend zero trust to OT environments, including ship control systems, autonomous platforms, and weapons guidance networks. These systems often operate in disconnected, contested, or resource-constrained environments, where traditional IT security measures fall short. Presumably, the use of AI in deployed combat systems would provide sufficient warning to unauthorized access by miscreants or saboteurs. In other words, preventing someone from physically taking control of, say, a missile weapons system.

Although AI’s role in these operational contexts is still evolving, officials view intelligent access control and real-time anomaly detection as critical components of secure combat systems for obvious reasons. The challenge to making it happen lies in ensuring that AI-enabled authentication mechanisms can function reliably in austere environments and under combat mission pressures. The Navy’s long-term goal is to implement a device-agnostic model for identity trust, ensuring that zero trust authentication works consistently across varied operational environments, whether a sailor is accessing a classified system aboard a submarine, or logging into a classified portal from a mobile device.

To achieve this, the Navy is exploring platform-agnostic risk scoring systems that evaluate factors like device posture, geolocation, session history, behavioral norms, and, presumably, is correlated to a user’s digitized security file. While these models are still in the evaluation phase, officials have confirmed that industry partners are involved in developing and testing context-aware access control tools. Public details on which commercial or government-developed tools are being used are sparse. However, the Navy has stressed the importance of explainable, auditable AI systems and has emphasized human oversight to prevent over-reliance on automated decision-making.

Navy cybersecurity officials are candid about the risks of overusing or misapplying AI. They warn of the potential for adversarial actors to spoof behavioral signals, poison training datasets, or deploy deepfakes and synthetic media to bypass biometric systems. Although there are no publicly confirmed contracts or projects awarded specifically by the Navy for deepfake detection technology, and the Navy has been mum on the matter, the need is well understood in Pentagon AI security circles. The Navy is known to be prioritizing AI models that can be audited and challenged by human operators, especially in high-consequence environments. Decision-support tools must complement, not replace, the judgment of trained analysts and operators.

The Navy’s zero trust and AI efforts are being coordinated closely with the Department of the Navy Chief Information Officer (DON CIO), Fleet Cyber Command, and the Defense Information Systems Agency. All collaborations that are designed to ensure that authentication protocols remain interoperable across service branches, mission domains, and security classifications. Navy officials have not confirmed specific budget increases for AI-driven, zero trust capabilities in the FY 2026 budget, but cybersecurity modernization remains a stated priority. The DON CIO’s Zero Trust Program serves as a strategic framework for implementation and includes six foundational pillars: identity, devices, network, applications and workloads, data, and visibility and analytics. 

Frequently Asked Questions (FAQS): 

Q: What is zero trust in the context of cybersecurity?

A: Zero trust is a security model that assumes no user or device, internal or external, should be inherently trusted. Access decisions are dynamically evaluated based on real-time risk assessments, ensuring continuous verification and context-aware authentication.

Q: How is the Navy using AI in its zero trust framework?

A: The Navy is using AI to analyze behavioral indicators for continuous identity verification. This includes evaluating patterns in login locations, time-of-day access, device usage, and frequency of interaction with enterprise resources to build dynamic user profiles and detect anomalies in real time.

Q: What is Flank Speed, and how does it support zero trust?

A: Flank Speed is the Navy’s enterprise Microsoft 365 cloud environment. It serves as a secure platform for collaboration, cloud storage, and productivity tools. Flank Speed supports zero trust by meeting technical requirements for continuous monitoring and policy enforcement at scale.

Q: What are the challenges of implementing zero trust in operational technology (OT) environments?

A: Implementing zero trust in OT environments is challenging because these systems often operate in disconnected, contested, or resource-constrained environments. The Navy is developing formal standards to extend zero trust to ship control systems, autonomous platforms, and weapons guidance networks.

Q: How does the Navy ensure the reliability of AI in austere environments and under combat mission pressures?

A: The Navy is exploring platform-agnostic risk scoring systems and emphasizing the importance of explainable, auditable AI systems. They are also prioritizing human oversight to prevent over-reliance on automated decision-making and ensure that AI models can function reliably in high-stakes scenarios. 

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