Developing an Optimized Intelligent Security Framework for Cyber-Physical Systems

It is therefore the intention of this study to provide an intelligent approach to security of CPS that has intelligent ML capability that can perform online analysis of data inputs to detect, avoid and neutralize cyber threats in CPS. The framework uses a multi-layer approach based on scheme for detection of anomalies and behavioural patterns integrated with basically reactive security responses. The model is hybridizing and use deep learning in order to balance the accuracy on threat detection with latency and resource utilize. CPS and components involve safe sharing of information as well as the decentralised trust and these are underpinned by Blockchain technology. In demonstrating that the CPS protection provided by the proposed framework is robust against emerging threats, theoretical testing and empirical analysis of specific cases have been conducted. The framework has been observed to over perform in areas of systems reliability and system durability. Based upon these discoveries, it is possible that CPS could in the future become safer from a comprehensive range of highly developed threats, and, at the same time, improve the stability rate and give more powerful protection.