Deception Technology Based Intrusion Protection and Detection Mechanism for Digital Substations: A Game Theoretical Approach

Abstract

Securing substations from cyber attacks is essential to safeguard critical power infrastructure. However, digital substations that are based on the IEC-61850 standard have Generic Object Oriented Substation Events (GOOSE) messages and Sampled Value (SV) messages that are time-critical and thus cannot be protected using encryption techniques. This work presents a study on deception technology (decoys) for mitigating cyber attacks on GOOSE message virtual LAN (VLAN) which is a non-observable strongly connected biography. In this paper, the deployment of defender decoys is proposed by defining observable subgraphs in the VLAN. The defender-attacker interaction is modeled as a single-leader singlefollower game with the defender as the leader. The optimal allocation of decoys for asset protection and attack detection is then formulated as a bi-level optimisation problem. Simultaneous allocation and sequential allocation of protection and detection decoys are considered for defender resource allocation. The existence of equilibrium of the defender-attacker game is proven. The model is illustrated in a 3-IED VLAN and performance is evaluated in a 12-IED VLAN system in the PSRC-I5 protection relay report. The results are compared with the zero-sum game model and it is found that the proposed model is capable of mitigating attacks in the GOOSE VLAN INDEX TERMS Deception technology, IEC-61850 standard, intrusion protection mechanism, intrusion detection mechanism, single-leader single-follower game. NOMENCLATURE VARIABLESDEVIKA JAY (Member, IEEE) received the B.Tech. degree in electrical and electronics engineering from the TKM College of Engineering, Kerala, India, in 2009, and the M.S. degree in power systems and the Ph.D. degree from the Indian Institute of Technology Madras, in 2013 and 2021, respectively. She was the Deputy Manager with Power Grid Corporation of India Ltd. She is currently the Founder and the CTO with Gridsentry Private Ltd. Her research interests include powergrid cybersecurity, power system economics, electricity markets, the application of game theory, and artificial intelligence in power system operation.

Deep Reinforcement Learning-Driven Mitigation of Adverse Effects of Cyber-Attacks on Electric Vehicle Charging Station

“…Also, 5G-based communication applications [9] in EVCS and related cybersecurity issues will be analyzed. Moreover, various game theoretic and dynamic programming approaches [26] along with powerful machine learning algorithms can be explored to develop optimal cyberattack-defense strategy in EVCS.…”