计算机应用 ›› 2013, Vol. 33 ›› Issue (02): 423-467.DOI: 10.3724/SP.J.1087.2013.00423

• 信息安全 • 上一篇    下一篇

基于无线传感器网络相关性的信息安全防御机制

洪勇,李平   

  1. 长沙理工大学 计算机与通信工程学院,长沙 410004
  • 收稿日期:2012-08-20 修回日期:2012-09-18 出版日期:2013-02-01 发布日期:2013-02-25
  • 通讯作者: 洪勇
  • 作者简介:洪勇(1989-),男,湖南衡阳人,硕士研究生,主要研究方向:传感器网络;
    李平(1972-),男,湖南长沙人,副教授,博士,CCF会员,主要研究方向:通信安全、传感器网络。
  • 基金资助:
    国家科技重大专项;中国科学院先导课题;国家863计划项目;湖南省科技重大专项

Information security defense mechanism based on wireless sensor network correlation

HONG Yong,LI Ping   

  1. Computer and Communication Engineering Institute, Changsha University of Science and Technology, Changsha Hunan 410004, China
  • Received:2012-08-20 Revised:2012-09-18 Online:2013-02-01 Published:2013-02-25
  • Contact: HONG Yong
  • Supported by:
    National Science and Technology Major Project

摘要: 当无线传感器网络中的传感节点被俘获时,可能发生内部攻击,从而致使系统信息安全缺失。针对这一情况,提出一种基于环状空间相关性模型的安全防御机制。基于环状空间相关性的模型,节点与节点之间进行信任值结合计算,相邻节点再对其进行信任评估,根据信任评估识别被俘获节点,间接去除被俘获节点信息,以达到信息的安全防御。仿真实验表明,经过机制改进后的各数据失真度有明显提高。该机制能有效识别并剔除虚假、恶意信息,提高系统的信息安全性。

关键词: 无线传感器网络, 虚假数据, 信息安全, 空间相关性, 失真度

Abstract: When the sensor nodes in Wireless Sensor Network (WSN) are captured, the internal attack may occur, thus resulting in a security deficiency of the system information. Regarding this, a security defense mechanism based on the annular space correlation model was proposed. The combined trust value between the nodes was calculated based on the model of the annular space, and the trust assessment again on its adjacent nodes was carried out. The captured nodes were recognized according to the trust assessment, and the information of the captured nodes were removed indirectly, thus achieving information security defense. The simulation results demonstrate that the data distortion has significantly improved by the optimized mechanism. This mechanism can effectively identify and remove errors and detrimental information, which improves the security of information in the system.

Key words: Wireless Sensor Network (WSN), false data, information security, spatial correlation, distortion degree

中图分类号: