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학술지 Intrusion Detection of NSM Based DoS Attacks Using Data Mining in Smart Grid
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저자
최경, Xinyi Chen, Shi Li, 김미희, 채기준, 나중찬
발행일
201210
출처
Energies, v.5 no.10, pp.4091-4109
ISSN
1996-1073
출판사
MDPI AG
DOI
https://dx.doi.org/10.3390/en5104091
협약과제
12MG1600, 스마트그리드 보안 관제기술 연구개발, 나중찬
초록
In this paper, we analyze the Network and System Management (NSM) requirements and NSM data objects for the intrusion detection of power systems; NSM is an IEC 62351-7 standard. We analyze a SYN flood attack and a buffer overflow attack to cause the Denial of Service (DoS) attack described in NSM. After mounting the attack in our attack testbed, we collect a data set, which is based on attributes for the attack. We then run several data mining methods with the data set using the Waikato Environment for Knowledge Analysis (WEKA). In the results, we select the decision tree algorithms with high detection rates, and choose key attributes in high level components of the trees. When we run several data mining methods again with the data set of chosen key attributes, the detection rates of most data mining methods are higher than before. We prove that our selected attack attributes, and the proposed detection process, are efficient and suitable for intrusion detection in the smart grid environment. © 2012 by the authors.
KSP 제안 키워드
Buffer overflow attack, Data mining(DM), Data mining methods, Data sets, Decision Tree(DT), Denial-of-service (DoS) attacks, IEC 62351-7, Network and system management(NSM), Power system, SYN flood attack, Smart grid environment
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