THE SECOND INTERNATIONAL CONFERENCE ON FORENSIC COMPUTER SCIENCE - ICoFCS 2007
Online ISBN: 978-85-65069-01-4, Print ISSN: 1980-1114, pp 18-23
DOI: 10.5769/C2007002 or http://dx.doi.org/10.5769/C2007002
Improving Detection Attacks in Electric Power System Critical Infrastructure Usign Rough Classification Algorith
By Maurílio Pereira Coutinho, Germano Lambert-Torres, Luiz Eduardo Borges da Silva, and Horst Lazarek
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Nowadays, National Critical Infrastructures play a fundamental role in modern society. The use of information technology (IT) to achieve service quality produces vulnerabilities and security threats. To safeguard against the threat of cyber-attacks, providers of Critical Infrastructure services also need to maintain the accuracy, assurance and integrity of their interdependent data networks. This paper presents a novel technique for improving the security of Electric Power System Critical Infrastructure by implementing anomaly detection methods to identify attacks and faults. By using Rough Sets Classification Algorithm, a set of rules can be defined to the anomaly detection process. This can be used for identify attacks and failures and, also, for improving state estimation.
Critical infrastructure protection, electric power system, SCADA , detecting attacks, rough set theory, data mining.
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