Visible to the public A Specification-Based Detection for Attacks in the Multi-Area System

TitleA Specification-Based Detection for Attacks in the Multi-Area System
Publication TypeConference Paper
Year of Publication2020
AuthorsSiu, J. Y., Panda, S. Kumar
Conference NameIECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society
Keywordsanomaly detection, automatic generation control, automatic generation control signals, cyber-attack events, cyber-physical grid, Damage Assessment, extensive power grid, false data injection attack detection, frequency control, frequency deviation, Frequency measurement, grid operation, multiarea system, novel specification-based method, power engineering computing, power grids, power system security, power system stability, protection measures, pubcrawl, resilience, Resiliency, risk management, rule-based method, security, security assessment, security of data, Smart grids, specification-based detection, system-level, three-area system model
AbstractIn the past decade, cyber-attack events on the power grid have proven to be sophisticated and advanced. These attacks led to severe consequences on the grid operation, such as equipment damage or power outages. Hence, it is more critical than ever to develop tools for security assessment and detection of anomalies in the cyber-physical grid. For an extensive power grid, it is complex to analyze the causes of frequency deviations. Besides, if the system is compromised, attackers can leverage on the frequency deviation to bypass existing protection measures of the grid. This paper aims to develop a novel specification-based method to detect False Data Injection Attacks (FDIAs) in the multi-area system. Firstly, we describe the implementation of a three-area system model. Next, we assess the risk and devise several intrusion scenarios. Specifically, we inject false data into the frequency measurement and Automatic Generation Control (AGC) signals. We then develop a rule-based method to detect anomalies at the system-level. Our simulation results proves that the proposed algorithm can detect FDIAs in the system.
Citation Keysiu_specification-based_2020