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计算机工程

• 安全技术 • 上一篇    下一篇

基于Beta信誉系统的鲁棒安全定位算法

胡峻峰,曹 军   

  1. (东北林业大学机电工程学院,哈尔滨 150040)
  • 收稿日期:2013-06-05 出版日期:2014-08-15 发布日期:2014-08-15
  • 作者简介:胡峻峰(1980－)，男，博士研究生，主研方向：网络安全，无线传感器网络；曹 军，教授、博士、博士生导师。
  • 基金项目:
    黑龙江省自然科学基金资助项目(QC2012C101)；中央高校基本科研业务费专项基金资助项目(DL10AB06)。 

Robust Secure Localization Algorithm Based on Beta Reputation System

HU Jun-feng,CAO Jun   

  1. (College of Mechanical and Electrical Engineering,Northeast Forest University,Harbin 150040,China)
  • Received:2013-06-05 Online:2014-08-15 Published:2014-08-15

PDF

944

被引次数

2

摘要： 针对存在恶意节点情况下的无线传感器网络(WSN)节点定位问题，提出基于Beta信誉系统(BRS)的鲁棒安全定位算法。在BRS基础上建立信任评估框架，传感器节点在多跳通信范围内将锚节点的最终信任值与所存储的阈值进行比较，从而降低WSN中恶意攻击的影响。采用基于泰勒级数展开的加权最小二乘法估算普通传感器节点的坐标，以识别WSN中的恶意锚节点，并提高节点定位精度。仿真结果表明，与RMLA2, RMLA1, Bilateration, t-TLS定位算法相比，该算法在恶意锚节点不存在串通的情况下定位精度分别提高约10%, 15%, 55%, 110%，在恶意节点串通的情况下定位精度分别提高约15%, 20%, 65%, 150%。

关键词: 无线传感器网络, Beta信誉系统, 安全定位, 恶意攻击, 泰勒级数, 最小二乘法

Abstract: Aiming at the problem of Wireless Sensor Network(WSN) node localization when exists malicious nodes,a robust secure localization algorithm based on Beta Reputation System(BRS) is proposed. The trust evaluation framework is established on the basis of BRS. Then, final trust value of anchor nodes are compared with stored threshold within the communication scope of multiple hops by sensor nodes and thus can reduce the impact of the malicious attackers in WSN. The weighted Taylor-series least squares method is employed to estimate the coordinates of sensor nodes, it can identify malicious anchor nodes of WSN and improve node localization accuracy. Simulation results show that the algorithm increases the localization accuracy by 10%, 15%, 55%, 110% at the condition without malicious node colluding and by 15%, 20%, 65%, 150% with malicious node colluding compared with RMLA2, RMLA1, Bilateration, t-TLS localization algorithm.

Key words: Wireless Sensor Network(WSN), Beta Reputation System(BRS), secure localization, malicious attack, Taylor series, least squares method

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