移动自组网中基于多约束和协同过滤动态信任机制*

由于具有分布式特性，导致移动自组网容易遭受攻击。为了增强移动自组网的安全性，建立一套适合自组织、无认证中心的节点信任评估模型是非常必要的。因此，提出了一种移动自组网中基于多约束和协同过滤的动态信任机制。其主要思想是在根据节点自身的经历的基础上，采用一个带多约束的信任更新算法来评估直接信任。其中：时间衰减因子保证了信任度随时间进行衰减；奖励因子保证了良好的节点应受到奖励；惩罚因子保证了恶意节点应受到惩罚。另外，采用协同过滤技术来评估推荐信任，以此来阻止不诚实的推荐。通过定量评估分析和模拟仿真，结果表明所提出的方法比Bayesian模型能更精确地计算节点之间的信任度和提高移动自组网的安全性。

Dynamic trust mechanism based on multi-constraints and collaborative filtering in mobile Ad hoc networks

Due to their distributed nature, mobile ad hoc networks (MANETs) are vulnerable to various attacks. To enhance security of MANETs, it is necessary to build a trust model for executions in a self-organizing and non-certified center network environment. This paper proposes a dynamic trust mechanism (DTM) based on multi-constraints and collaborative filtering in MANETs. The main idea of our method is to introduce a trust updating algorithm with multi-constraints (time aging factor ensures that the trust fades with time; rewards factor ensures that good peers deserve to be rewarded; and penalty factor ensures that the selfish or the malicious deserve to be punished) to assess direct trust by self-experience of nodes, and to adopt collaborative filtering technique to evaluate recommendation trust in order to prevent false recommendations. The analytic results show that DTM not only can compute trust between nodes more precisely than Bayesian model, but also can improve security of MANETs through quantitative evaluation analysis and extensive simulations.