Securing Military Networks with AI-Powered ZTNA

Authors:

Dr.S.Brindha, Ms.D.Priya,Sharvanthvadivelan

 Department of Computer Networking

PSG Polytechnic College, Coimbatore, Tamil Nadu

Abstract — Military communication infrastructure faces unprecedented cyber threats that demand far more than traditional perimeter-based security approaches. This paper presents an AI-Powered Zero Trust Network Access (ZTNA) framework specifically designed for military networks, integrating machine learning-based threat detection, multi-factor authentication (MFA), and AES-256 encryption. The proposed system enforces a "Never Trust, Always Verify" paradigm by continuously validating user identity, device health, and network context before granting granular resource access. An ensemble AI model monitors real-time traffic patterns to detect anomalies and potential intrusions with a detection accuracy of 97.4% and a false-positive rate of 2.1%. Experimental results demonstrate significant improvements in security posture, latency, and operational scalability compared to conventional VPN and standard ZTNA implementations. The framework is applicable across defence communications, government systems, healthcare, and financial sectors.

Keywords: Zero Trust Network Access, Artificial Intelligence, Military Networks, AES Encryption, Multi-Factor Authentication, Anomaly Detection, Cybersecurity.