基于信誉系统及数据噪声点检测技术的无线传感器网络节点安全模型

Node security model for wireless sensor networks based on a reputation system and data noise point detection technique

随着对无线传感器网络的广泛研究与应用,用户对传感器节点的安全性要求日益提高。由于传统基于密码学的信息安全技术并不能够完美地解决传感器节点面临的复杂安全威胁,信誉系统已经被引入到无线传感器网络中,对节点安全情况进行周期性评估,并分配相应的信誉值。由于信誉系统很难分辨一些节点的某些行为是否处于正常区间如监测数据是否准确,进而导致某些传感器节点能够躲避信誉系统的监测,对用户决策产生不良影响。本文提出了一种结合信誉系统和噪声点检测技术的无线传感器网络节点安全模型。一方面,网络中的信誉系统模块为噪声点检测模块提供数据支撑,以便高效检测到噪声点数据;另一方面,噪声点检测模块对信誉系统进行反馈,加速节点信誉值的收敛,提高系统效率。一系列的仿真表明,相比于传统信誉系统模型,改进后的节点安全模型能够同时检测到网络攻击和数据攻击,同时该模型具有更高的收敛速度。

The increased number of wireless sensor networks requires security for the sensor nodes. Since traditional information security systems based on cryptography cannot serve the complex safety issues threatening sensor nodes, the reputation system has been introduced into wireless sensor networks to periodically evaluate security nodes and assign reputation values. However, the reputation system cannot always distinguish some abnormal behavior in the sensor nodes, such as the monitoring data accuracy. As a result, some nodes can avoid monitoring by the reputation system which will affect user decisions. This paper presents a wirelesssensor network node security model combining the reputation system with data noise detection. The reputation system provides the node reputations to the data noise detection model to more effectively detect data noise. The data noise detection model then feeds information back to the reputation system which accelerates the convergence rate of the reputation system. Simulations show that this node security model can simultaneously detect network and data attacks better than the traditional credit system model with a higher convergence rate.