Intrusion Detection on Apache Spark Platform in Big data and Machine Learning Techniques

Abstract

With the rising cyber-physical power systems and emerging danger of cyber-attacks, the traditional power services are faced with higher risks of being compromised, as vulnerabilities in cyber communications can be broken to cause material damage. Therefore, adjustment needs to be made in the present control scheme plan methods to moderate the impact of possible attacks on service quality. This paper, focuses on the service of synchronized source-load contribution in main frequency regulation, a weakness study is performed with model the attack intrusion process, and the risk review of the service is made by further model the attack impacts on the service’s bodily things. On that basis, the customary synchronized reserve allotment optimization model is adapted and the allocation scheme is correct according to the cyber-attack impact. The proposed alteration methods are validating through a case study, showing efficiency in defensive alongside the cyber-attack impacts.