BALANCING INNOVATION AND RISK: AI CYBER THREATS AND THE FUTURE OF CLASSIFIED DOCUMENT SECURITY
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Abstract
As artificial intelligence (AI) continues to reshape global technological landscapes, its
integration into classified document management systems presents both unprecedented
opportunities and emerging threats. While AI tools enhance document indexing, real-time
threat detection, and access control, they are also being weaponized through adversarial
machine learning, deepfake phishing, and AI-powered malware. This dual-use dilemma has
raised concerns about the resilience of traditional cybersecurity frameworks in safeguarding
sensitive national data. Recent incidents involving AI-driven data exfiltration and polymorphic
threats have demonstrated the need for robust, intelligent defense systems that can adapt to
evolving threat vectors. This paper investigates the spectrum of AI-enabled threats to classified
document security, alongside the growing use of AI for anomaly detection, access monitoring,
and privacy-preserving analytics. Drawing upon recent research and case reports, it emphasizes
the necessity of balancing innovation with risk management in sensitive information
ecosystems. The study concludes by recommending ethical, technical, and policy-driven
safeguards to future-proof classified systems in the age of autonomous cyber threats.