Visible to the public SCORE: A Security-Oriented Cyber-Physical Optimal Response Engine

TitleSCORE: A Security-Oriented Cyber-Physical Optimal Response Engine
Publication TypeConference Paper
Year of Publication2019
AuthorsSahu, Abhijeet, Huang, Hao, Davis, Katherine, Zonouz, Saman
Conference Name2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
ISBN Number978-1-5386-8099-5
Keywordsattack escalation, automatic decision making engine, automatic optimal response systems, Cascading Failures, Computational modeling, CPS Resilience, cyber physical systems, cyber-physical decision support system, Cyber-physical systems, cyberattack, decision making, Decision support systems, Engines, hybrid cyber-physical states, Markov Decision Process, Markov processes, MDP, optimal response, policy iteration techniques, power engineering computing, power system operators, power system reliability, power system resilience, power system security, power system stability, pubcrawl, pure cyber-physical states, Relays, resilience, Resiliency, security of data, security-oriented cyber-physical optimal response engine, Smart grids, state transition model, substation power systems, Substations, System recovery, transmission line overflow, value and policy iteration, value iteration techniques

Automatic optimal response systems are essential for preserving power system resilience and ensuring faster recovery from emergency under cyber compromise. Numerous research works have developed such response engine for cyber and physical system recovery separately. In this paper, we propose a novel cyber-physical decision support system, SCORE, that computes optimal actions considering pure and hybrid cyber-physical states, using Markov Decision Process (MDP). Such an automatic decision making engine can assist power system operators and network administrators to make a faster response to prevent cascading failures and attack escalation respectively. The hybrid nature of the engine makes the reward and state transition model of the MDP unique. Value iteration and policy iteration techniques are used to compute the optimal actions. Tests are performed on three and five substation power systems to recover from attacks that compromise relays to cause transmission line overflow. The paper also analyses the impact of reward and state transition model on computation. Corresponding results verify the efficacy of the proposed engine.

Citation Keysahu_score_2019