Blockchain-Enabled IDPS and Federated Learning for Enhancing CPS Security against Advanced Persistent Threats in Zero Trust Architectures

The growing integration of edge computing and Internet of Things devices in Industry 4.0 has heightened the complexity and sophistication of advanced persistent threats (APTs), challenging the effectiveness of traditional security solutions. To safeguard cyber-physical systems (CPS) within zero trust architecture environments, this study introduces a novel federated learning and blockchain-enabled intrusion detection and prevention system (FL-BIDPS). Leveraging blockchain technology and federated learning, FL-BIDPS ensures secure, immutable logging and verification while preserving privacy through decentralized threat detection. By enabling collaborative threat detection without the need to transfer raw data, the solution minimizes the risk of data breaches. The integration of blockchain technology guarantees that all security incidents are recorded in an immutable, tamper-proof manner. Additionally, hypothetical evaluations demonstrate the system's enhanced efficiency in detecting and preventing APTs, alongside significant improvements in privacy and security features. This innovative approach offers a dependable, scalable, and sustainable solution for protecting CPS in an increasingly vulnerable and interconnected landscape, overcoming the limitations of traditional security methods.