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Intrusion detection of NSM based DoS attacks using data mining in smart grid

Title
Intrusion detection of NSM based DoS attacks using data mining in smart grid
Authors
Choi K.Chen X.Li S.Kim M.Chae K.Na J.C.
Ewha Authors
채기준
SCOPUS Author ID
채기준scopus
Issue Date
2012
Journal Title
Energies
ISSN
1996-1073JCR Link
Citation
vol. 5, no. 10, pp. 4091 - 4109
Indexed
SCIE; SCOPUS WOS scopus
Abstract
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.
DOI
10.3390/en5104091
Appears in Collections:
엘텍공과대학 > 컴퓨터공학과 > Journal papers
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