Bayesian-driven autonomous defense adaptive consensus optimisation for blockchain networks.

Blockchain networks have revolutionized decentralized applications but remain vulnerable to evolving security threats due to their reliance on static consensus mechanisms that cannot adapt to changing threat landscapes. This paper addresses this critical security gap by proposing Autonomous Defense-Adaptive Consensus Optimisation for Blockchain Networks (ADACON), an original framework for the dynamic adjustment of consensus mechanisms based on Bayesian threat detection. The research investigates how real-time adaptation between multiple consensus protocols can enhance blockchain resilience while maintaining performance. The approach integrates a Bayesian Threat Detector, Consensus Adapter, and Network State monitor in a modular architecture that continuously assesses network conditions and switches between five consensus mechanisms (PoW, PoS, PBFT, PoA, DPoS) as threats emerge. The framework was evaluated through comprehensive simulations involving 1,000 nodes, testing response to six distinct attack vectors, including Sybil, DoS, Byzantine, Eclipse, Majority, and Routing attacks. Results demonstrate that ADACON effectively identifies and responds to varied attacks with a latency of 29.7 ms and throughput of 833 TPS). Statistical validation across five independent simulation runs (seeds 5-9) confirmed framework reliability with consistent performance metrics (CV < 7.1% for latency, 5.4% for throughput). Delegated Proof of Stake emerged as the most frequently selected mechanism (23.2%) due to its balanced performance across multiple security dimensions. Significantly, the system exhibited greater adaptability and attack coverage than existing hybrid approaches. The previous high switching frequency was reduced by using hysteresis, i.e., by providing dwell time and an improved threshold that avoids unnecessary switching. The study concludes that dynamic consensus adaptation offers substantial security advantages for blockchain networks, particularly in high-security environments like financial systems and critical infrastructure. However, further research must focus on optimizing switching frequency and developing secure transition protocols to maximize effectiveness. ADACON represents an incremental extension tested toward more resilient blockchain systems that can autonomously respond to emerging threats while balancing security, performance, and resource utilization.