<![CDATA[Defense supply chains face critical security challenges including counterfeit components, unauthorized access, data tampering, and supply chain attacks that compromise operational integrity and national security. Existing blockchain implementations suffer from limited scalability, inadequate threat detection mechanisms, and insufficient integration with modern AI technologies for real-time security monitoring. This research develops an AI-Enhanced Blockchain Security Framework combining smart contracts with distributed ledger technology specifically designed for defense supply chain management. The framework employs multi-signature authentication, cryptographic verification, and machine learning-based anomaly detection across a three-layer architecture (blockchain layer, security layer, analytics layer). Validation using the DataCo supply chain dataset (180K operations) and Backstabber's knife collection attack patterns (174 documented attacks) demonstrates 94.7% attack detection accuracy, 87.3% reduction in unauthorized access attempts, and 99.2% data integrity verification rate. The system achieved 850 transactions per second (TPS) throughput with 1.8-second average latency and 40% cost reduction compared to traditional centralized systems. Smart contract execution showed 99.96% reliability across 10,000 test scenarios with automated enforcement of security policies. Statistical validation confirmed significant superiority over conventional approaches (p<0.001). Future work includes quantum-resistant cryptography, federated learning for privacy-preserving analytics, cross-chain interoperability, and integration with IoT sensors for real-time supply chain monitoring.]]>
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