AI Integrating Blockchain with Smart Grid Cyber Security: Models, Methods, and Open Research Issues
Ashish Reddy Kotla
Abstract
Frequent digitalization of power systems has increased the areas of cyber attack on smart grids that require more developed security frameworks capable of responding to cyber and physical threats. The paper is a detailed discussion on the implementation of Artificial Intelligence (AI) and Block chain in improving the cyber security of smart grids. To prevent new cyber threats, we suggest a new hybrid security model, which uses AI-based anomaly detection and decentralized integrity checks, based on block chains. The architecture is a fusion of machine learning based real time threat detection and immutable block chain ledgers to keep transactions safe and under control. We prove with the help of the performance evaluation and case studies that the model is efficient in the detection of false data injection, distributed denial of service (DDOS) attacks, and other advanced threats. The paper also cites major issues such as the scalability, interoperability, and computational overhead, as well as outlining opportunities of future research in resilient smart grid infrastructure. We have found out that the AI-block chain implementation has the potential to enhance the accuracy of threat detection up to 30 percent relative to traditional approaches as well as integrity and transparency of data management in smart grids.