Design Of Intelligent Countermeasure System for Power System Network Security Defense

Abstract

In an increasingly interconnected world, the convergence of power system networks and biometric-based biomedical applications presents unique challenges for data protection and privacy. This research endeavors to conceptualize and design an intelligent countermeasure system that serves as a robust defense mechanism for enhancing security in this complex ecosystem. The proposed system incorporates biometric authentication techniques to fortify user access controls, implements advanced encryption methods for safeguarding sensitive biomedical data, and intrusion detection and prevention mechanisms to thwart cyber threats. This paper proposed an Integrated Probabilistic Regression Cryptographic Classifier (IPRCC) for data protection and privacy in biometric data for power system devices for biomedical applications. The IPRCC combines probabilistic regression techniques for data analysis with cryptographic methods to fortify the security and privacy of biometric data used within power system devices for biomedical applications. To secure biometric data, IPRCC integrates cryptographic techniques. Cryptography involves encoding information in a way that only authorized parties can decode and understand it. IPRCC incorporates a classifier as part of its security framework. The classifier is used to make decisions or classifications based on the analyzed biometric data. The IPRCC includes enhanced data protection, improved privacy, and increased security for biometric data. The Integrated Probabilistic Regression Cryptographic Classifier (IPRCC) is a sophisticated security system that combines probabilistic regression modeling and cryptographic techniques to protect biometric data used in biomedical applications, especially when integrated with power system devices. Simulation results demonstrated that the proposed IPRCC model exhibits an improved attack detection rate of 99%.