{"title":"基于高效聚类技术的客户端信任检测、发现与评估研究综述","authors":"K. Sudharson, N. Partheeban","doi":"10.5121/IJCSES.2012.3107","DOIUrl":null,"url":null,"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.","PeriodicalId":415526,"journal":{"name":"International Journal of Computer Science & Engineering Survey","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A SURVEY ON DETECT - DISCOVERING AND EVALUATING TRUST USING EFFICIENT CLUSTERING TECHNIQUE FOR MANET S\",\"authors\":\"K. Sudharson, N. Partheeban\",\"doi\":\"10.5121/IJCSES.2012.3107\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":415526,\"journal\":{\"name\":\"International Journal of Computer Science & Engineering Survey\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-02-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computer Science & Engineering Survey\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5121/IJCSES.2012.3107\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computer Science & Engineering Survey","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/IJCSES.2012.3107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A SURVEY ON DETECT - DISCOVERING AND EVALUATING TRUST USING EFFICIENT CLUSTERING TECHNIQUE FOR MANET S
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.