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Unsupervised Machine Learning-Based Detection of Covert Data Integrity Assault in Smart Grid Networks Utilizing Isolation Forest

IEEE transactions on information forensics and security, v.14 no.10, 2019년, pp.2765 - 2777  

Ahmed, Saeed (University of Ulsan, Ulsan, South Korea) ,  Lee, Youngdoo (University of Ulsan, Ulsan, South Korea) ,  Hyun, Seung-Ho (University of Ulsan, Ulsan, South Korea) ,  Koo, Insoo (University of Ulsan, Ulsan, South Korea)

Abstract AI-Helper 아이콘AI-Helper

Being one of the most multifaceted cyber-physical systems, smart grids (SGs) are arguably more prone to cyber-threats. A covert data integrity assault (CDIA) on a communications network may be lethal to the reliability and safety of SG operations. They are intelligently designed to sidestep the trad...

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