首页    期刊浏览 2024年10月05日 星期六
登录注册

文章基本信息

  • 标题:Trust-Based Anomaly Detection in Emerging Sensor Networks
  • 本地全文:下载
  • 作者:Renyong Wu ; Xue Deng ; Rongxing Lu
  • 期刊名称:International Journal of Distributed Sensor Networks
  • 印刷版ISSN:1550-1329
  • 电子版ISSN:1550-1477
  • 出版年度:2015
  • 卷号:2015
  • DOI:10.1155/2015/363569
  • 出版社:Hindawi Publishing Corporation
  • 摘要:Wireless sensor networks (WSNs) consist of a large number of small-size, energy-constrained nodes and generally are deployed to monitor surrounding situation or relay generated packets in other devices. However, due to the openness of wireless media and the inborn self-organization feature of WSNs, that is, frequent interoperations among neighbouring nodes, network security has been tightly related to data credibility and/or transmission reliability, thus trust evaluation of network nodes is becoming another interesting issue. Obviously, how to describe node’s behaviors and how to integrate various characteristics to make the final decision are two major research aspects of trust model. In this paper, a new trust model is proposed to detect anomaly nodes based on fuzzy theory and revised evidence theory. By monitoring the behaviors of the evaluated nodes with multidimensional characteristics and integrating these pieces of information, the malicious nodes in a network can be identified and the normal operation of the whole network can be verified. In addition, to accelerate the detection process, a weighting judgment mechanism is adopted to deal with the uncertain states of evaluated nodes. Finally extensive simulations are conducted, and the results demonstrate that the proposed trust model can achieve higher detection ratio of malicious nodes in comparison with the previously reported results.
国家哲学社会科学文献中心版权所有