Detekcija malicioznih napada na elektroenergetski sistem korišćenjem sinergije statičkog i dinamičkog estimatora stanja
Detection of False Data Injection Attacks on Power System using a synergybased approach between static and dynamic state estimators
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U ovoj doktorskoj disertaciji predložena je nova metoda za detekciju malicioznih napada injektiranjem loših merenja na elektroenergetski sistem. Predloženi algoritam baziran je na sinergiji statičke i dinamičke estimacije stanja, i u stanju je da detektuje ovaj tip napada u realnom vremenu, za najkritičniji scenario gde napadač ima potpuno znanje o sistemu, i neograničen pristup resursima.
This PhD thesis proposes a novel method for detection of malicious false data injection attacks on power system. The proposed algorithm is based on synergy between static and dynamic state estimators, and is capable of detecting the forementioned attacks in real time, for the most critical scenarios, where an attacker has complete knowledge about the compromised power system and unlimited resources to stage an attack.