Harbin Institute of Technology (Shenzhen), School of Computer, Shenzhen 518055, China.
Cyberspace Security Research Center, Peng Cheng Laboratory, Shenzhen 518000, China.
Sensors (Basel). 2020 Mar 12;20(6):1592. doi: 10.3390/s20061592.
The trust computing mechanism has an increasing role in the cooperative work of wireless sensor networks. However, the computing speed, resource overhead, and anti-collaborative attack ability of a trust mechanism itself are three key challenging issues for any open and resource-constrained wireless sensor networks. In this study, we propose a fast, resource-saving, and anti-collaborative attack trust computing scheme (FRAT) based on across-validation mechanism for clustered wireless sensor networks. First, according to the inherent relationship among three network entities (which are made up of three types of network nodes, namely base stations, cluster heads, and cluster members), we propose the cross-validation mechanism, which is effective and reliable against collaborative attacks caused by malicious nodes. Then, we adopt a fast and resource-saving trust computing scheme for cooperation between between cluster heads or cluster members. This scheme is suitable for wireless sensor networks because it facilitates resource-saving. Through theoretical analysis and experiments, the feasibility and effectiveness of the trust computing scheme proposed in this study are verified.
信任计算机制在无线传感器网络的协作工作中发挥着越来越重要的作用。然而，信任机制本身的计算速度、资源开销和抗协作攻击能力是任何开放的、资源受限的无线传感器网络面临的三个关键挑战问题。在这项研究中，我们提出了一种基于跨验证机制的用于分簇无线传感器网络的快速、节省资源和抗协作攻击的信任计算方案（FRAT）。首先，根据三个网络实体（由三种类型的网络节点组成，即基站、簇头和簇成员）之间的内在关系，我们提出了跨验证机制，该机制对恶意节点引起的协作攻击是有效和可靠的。然后，我们采用了一种快速、节省资源的簇头或簇成员之间合作的信任计算方案。该方案适用于无线传感器网络，因为它有利于节省资源。通过理论分析和实验，验证了所提出的信任计算方案的可行性和有效性。
