Analyzing and predicting behavior of node can lead to more secure and more appropriate defense mechanism for attackers in the Mobile Adhoc Network. In this work, models for dynamic recommendation based on fuzzy clustering techniques, applicable to nodes that are currently participate in the transmission of Adhoc Network. The approach focuses on both aspects of MANET mining and behavioral mining. Applying fuzzy clustering and mining techniques, the model infers the node's preferences from transmission logs. The fuzzy clustering approach, in this study, provides the possibility of capturing the uncertainty among node's behaviors. The results shown are promising and proved that integrating fuzzy approach provide us with more interesting and useful patterns which consequently making the recommender system more functional and robust. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2012.
CITATION STYLE
Sudharson, K., & Parthipan, V. (2012). A survey on ATTACK - anti terrorism technique for ADHOC using clustering and knowledge extraction. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 85, pp. 508–514). https://doi.org/10.1007/978-3-642-27308-7_54
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