Volume 6 Number 11 (Nov. 2011)
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JSW 2011 Vol.6(11): 2159-2166 ISSN: 1796-217X
doi: 10.4304/jsw.6.11.2159-2166

Information Security Risk Assessment Based on Information Measure and Fuzzy Clustering

Guo-hong Gao, Xue-yong Li, Bao-jian Zhang, Wen-xian Xiao
School of Information Engineer, Henan Institute of Science and Technology , Henan Xinxiang, 453003, China

Abstract—To address the problems of lack of training data and difficult to find optimal value in information security risk assessment, this paper applying a new information measure method and fuzzy clustering in information security risk assessment. The new method quantifies risk factors of all data and the dependence degree of safety with the mutual information computing. Then search optimal points in each degree of risk as original center points of Kmeans clustering algorithm, and use the K-means clustering algorithm for data classification. This method has less computation, and it can overcome the K-means’s shortcoming of sensitive to initial value and problem of nonlinear and complexity of information security risk assessment. Experimental results show the effectiveness of our method.

Index Terms—Information security, Risk assessment, Information Measure, Fuzzy Clustering


Cite: Guo-hong Gao, Xue-yong Li, Bao-jian Zhang, Wen-xian Xiao, "Information Security Risk Assessment Based on Information Measure and Fuzzy Clustering," Journal of Software vol. 6, no. 11, pp. 2159-2166, 2011.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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