Selective forwarding attack detection and network recovery mechanism based on cloud-edge cooperation in software-defined wireless sensor network

Abstract

A software-defined wireless sensor network can dynamically configure the nodes in a network according to the demand of the application layer. In practical applications, such as environmental monitoring, the nodes in a wireless sensor network(WSN) are deployed in the field environment on a large scale, and the data rely on multihop transmission to reach the sink node. The data extremely easy to selective forwarding attacks during data transmission. Therefore, this study analyzes the models of selective forwarding attacks and proposes an abnormal node detection method, which includes a node behavior measurement scheme and trust-value evaluation mechanism. In addition, the application of a software-defined network (SDN) presents increasing network delay. Hence, herein a network recovery mechanism was designed based on cloud-edge cooperation to ensure the rapid recovery of the network after identifying the abnormal nodes. Moreover, experiments were conducted using simulation software and actual hardware. We verified the effectiveness of the proposed scheme. The experimental results revealed that the proposed method can effectively identify abnormal nodes, reduce the packet dropping ratio and shorten the network recovery delay by 77.2%. The research in this paper solves the security problem of SDWSN.