Intuitionistic Fuzzy Reasoning Method in Traffic Anomaly Detection

Fan Xiao-shi; Lei Ying-jie; Wang Ya-nan; Guo Xin-peng

doi:10.11999/JEIT150023

Volume 37 Issue 9

Sep. 2015

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Article Navigation > Journal of Electronics & Information Technology > 2015 > 37(9): 2218-2224

Fan Xiao-shi, Lei Ying-jie, Wang Ya-nan, Guo Xin-peng. Intuitionistic Fuzzy Reasoning Method in Traffic Anomaly Detection[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2218-2224. doi: 10.11999/JEIT150023

Citation:

Fan Xiao-shi, Lei Ying-jie, Wang Ya-nan, Guo Xin-peng. Intuitionistic Fuzzy Reasoning Method in Traffic Anomaly Detection[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2218-2224. doi: 10.11999/JEIT150023

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Intuitionistic Fuzzy Reasoning Method in Traffic Anomaly Detection

doi: 10.11999/JEIT150023

Received Date: 2015-01-06
Rev Recd Date: 2015-03-18
Publish Date: 2015-09-19

Abstract

Abstract

Aiming at the characteristics of uncertainty and fuzziness of the network traffic attribute, an Intuitionistic Fuzzy Reasoning Theory (IFRT) is introduced to the anomaly detection field. A method of IFRT detection based on the inclusion degree is proposed. Firstly, the membership and non-membership functions of attributes in anomaly detection are designed. Secondly, the intensity similarity measure method based on the inclusion degree is presented and the rules library is generated. And then, the FMP rules of the IFRT are presented. Finally, an anomaly detection based on the IFRT is constructed. The validity is checked by experiment on the standard detection dataset KDD99, compared with other traditional theory, the IFRT anomaly detection method performs better than others.
- Network,
- Information security,
- Intuitionistic fuzzy sets,
- Anomaly detection,
- Intuitionistic Fuzzy Reasoning (IFR),
- Feature attribute,
- Inclusion degree

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References(21)

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