AI-Driven Cyber Threat Intelligence with Blockchain: A Federated and Privacy-Preserving Approach (FPPA) for Secure Defense

The growing complexity of cyber threats requires a smart, decentralized, and tamper-proof method of Cyber Threat Intelligence (CTI). This work suggests a new combination of Blockchain and Artificial Intelligence (AI) to improve security, transparency, and real-time threat protection in cybersecurity environments. Our method utilizes blockchain's immutability to provide reliable CTI sharing and AI-based threat analytics for adaptive defense. In this work, a Smart Contract-based AI platform has been designed to facilitate automated threat validation, anomaly detection, and predictive security responses. The platform leverages Federated Learning (FL) and Generative Adversarial Networks (GANs) to ensure privacy-preserving and adversarial-resilient intelligence sharing. Our blockchain-driven decentralized platform eliminates single point of failure, enhances traceability, and promotes stakeholder collaboration in contrast to conventional centralized CTI platforms (e.g. G. governments, businesses, and security researchers). Robustness against adversarial attacks, reduced false positives, and improved detection accuracy are demonstrated by extensive experimental evaluation on real cyberattack data sets. The effectiveness of our solution in thwarting Advanced Persistent Threats (APTs) and zero-day attacks is demonstrated through comparative benchmarking with existing CTI frameworks. As we lay the groundwork for a next-generation, AI-powered blockchain platform for cybersecurity, also consider scalability, regulatory compliance, and integration challenges.