Advances in Computer Science and Information Technology. Computer Science and Engineering. Second International Conference, CCSIT 2012, Bangalore, India, January 2-4, 2012. Proceedings, Part II

Research Article

A Survey on ATTACK – nti errorism echnique for DHOC Using lustering and nowledge Extraction

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  • @INPROCEEDINGS{10.1007/978-3-642-27308-7_54,
        author={K. Sudharson and V. Parthipan},
        title={A Survey on ATTACK -- nti errorism echnique for DHOC Using lustering and nowledge Extraction},
        proceedings={Advances in Computer Science and Information Technology. Computer Science and Engineering. Second International Conference, CCSIT 2012, Bangalore, India, January 2-4, 2012. Proceedings, Part II},
        proceedings_a={CCSIT PATR II},
        year={2012},
        month={11},
        keywords={MANET Mining Fuzzy Clustering Knowledge Discovery},
        doi={10.1007/978-3-642-27308-7_54}
    }
    
  • K. Sudharson
    V. Parthipan
    Year: 2012
    A Survey on ATTACK – nti errorism echnique for DHOC Using lustering and nowledge Extraction
    CCSIT PATR II
    Springer
    DOI: 10.1007/978-3-642-27308-7_54
K. Sudharson1,*, V. Parthipan2,*
  • 1: S.A. Engineering College
  • 2: Thirumalai Engineering College
*Contact email: mail@sudharson.in, parthipansp@gmail.com

Abstract

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.