An HMM-Based Anomaly Detection Approach for SCADA Systems
作者： Kyriakos Stefanidis , Artemios G. Voyiatzis
DOI: 10.1007/978-3-319-45931-8_6
关键词: Computer science 、 Protocol data unit 、 SCADA 、 Benchmark (computing) 、 Data mining 、 Anomaly detection 、 Hidden Markov model 、 Intrusion detection system 、 Exploit 、 Industrial control system
摘要: We describe the architecture of an anomaly detection system based on Hidden Markov Model (HMM) for intrusion in Industrial Control Systems (ICS) and especially SCADA systems interconnected using TCP/IP. The proposed exploits unique characteristics ICS networks protocols to efficiently detect multiple attack vectors. evaluate terms accuracy as reference datasets made available by other researchers. These refer real industrial contain a variety identified benchmark our findings against large set machine learning algorithms demonstrate that proposal exhibits superior performance characteristics.
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