School of Instrument Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics (Beihang University), Beijing 100191, China.
Sensors (Basel). 2011;11(2):1345-60. doi: 10.3390/s110201345. Epub 2011 Jan 25.
For wireless sensor networks (WSNs), many factors, such as mutual interference of wireless links, battlefield applications and nodes exposed to the environment without good physical protection, result in the sensor nodes being more vulnerable to be attacked and compromised. In order to address this network security problem, a novel trust evaluation algorithm defined as NBBTE (Node Behavioral Strategies Banding Belief Theory of the Trust Evaluation Algorithm) is proposed, which integrates the approach of nodes behavioral strategies and modified evidence theory. According to the behaviors of sensor nodes, a variety of trust factors and coefficients related to the network application are established to obtain direct and indirect trust values through calculating weighted average of trust factors. Meanwhile, the fuzzy set method is applied to form the basic input vector of evidence. On this basis, the evidence difference is calculated between the indirect and direct trust values, which link the revised D-S evidence combination rule to finally synthesize integrated trust value of nodes. The simulation results show that NBBTE can effectively identify malicious nodes and reflects the characteristic of trust value that 'hard to acquire and easy to lose'. Furthermore, it is obvious that the proposed scheme has an outstanding advantage in terms of illustrating the real contribution of different nodes to trust evaluation.
对于无线传感器网络（WSNs），许多因素，如无线链路的相互干扰、战场应用以及暴露在环境中没有良好物理保护的节点，导致传感器节点更容易受到攻击和被攻破。为了解决这个网络安全问题，提出了一种新的信任评估算法，定义为 NBBTE（基于节点行为策略的信任评估算法的置信度理论），它集成了节点行为策略的方法和改进的证据理论。根据传感器节点的行为，建立了与网络应用相关的各种信任因素和系数，通过计算信任因素的加权平均值来获得直接和间接信任值。同时，应用模糊集方法来形成证据的基本输入向量。在此基础上，计算间接和直接信任值之间的证据差异，将修正的 D-S 证据组合规则与最终合成节点的综合信任值联系起来。仿真结果表明，NBBTE 可以有效地识别恶意节点，并反映信任值的特征，即“难以获取，易于丢失”。此外，该方案在说明不同节点对信任评估的实际贡献方面具有明显的优势。
