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Intrusion Detection Method for MANET Based on Graph Theory |
ZHANG Bingtao①② WANG Xiaopeng① WANG Lücheng① ZHANG Zhonglin① LI Yanlin③ LIU Hu① |
①(School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070 China)
②(School of Information Science and Engineering, Lanzhou University, Lanzhou 730000 China)
③(Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000 China) |
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Abstract Mobile Ad hoc NETwork (MANET) is vulnerable to various security threats, and intrusion detection is an effective guarantee for its safe operation. However, existing methods mainly focus on feature selection and feature weighting, and ignore the potential association among features. To solve this problem, an intrusion detection method for MANET based on graph theory is proposed. First of all, nine features are selected as nodes based on the analysis of typical attack behavior, and the edges among nodes are determined according to Euclidean distance so as to build the structure diagram. Secondly, the scale attributes of neighborhood nodes and the degree of closeness attributes among nodes are considered to explore (i.e. feature) the correlation among nodes, then the statistical properties degree distribution and clustering coefficient of graph theory are used to realize the above two attributes. Finally, contrasting experimental results show that compared with the traditional methods, the average detection rate and false detection rate of new method are improved by 10.15% and reduced by 1.8% respectively.
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Received: 25 July 2017
Published: 02 April 2018
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Fund:The National Natural Science Foundation of China (61761027, 61261029, 61662043), The Yong Scholar Fund of Lanzhou Jiaotong University (2016004) |
Corresponding Authors:
ZHANG Bingtao
E-mail: zhangbingtao321@163.com
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