Consensus-Based Intrusion Detection for the Electric Power Grid Control System
Amullen, E., Keel, L.
We study false data injection attacks that affect state estimation in the power grid. We consider a class of false data injection attacks that cannot be detected by conventional bad data detection schemes employed in the power grid and propose a distributed agent-based system for detecting and mitigating these attacks. In the agent-based framework, software-based agents are deployed at substations within the power grid to carry out (1) distributed state estimation (2) Ensure secure state estimation by detecting maliciously injected data and (3) Communicate with adjacent agents to coordinate detection efforts. To coordinate results among agents in a time bound fashion, we propose a consensus-based information exchange strategy in which agents share data with neighboring agents and arrive at a consensus value. To detect attacks, the consensus value is evaluated against a threshold. To demonstrate the effectiveness of the agent-based detection strategy, we simulate 1000 attack scenarios against the IEEE 9-bus, 14-bus, and 30-bus test power networks using MATPOWER and show that agents successfully detect at least 98% of the attacks.
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