Security in IoT Mesh Networks Based on Trust Similarity

Abstract

Internet of Things (IoT) Mesh networks are becoming very popular to enable IoT devices to communicate without relying on dedicated PC services. The Internet of Things (IoT) implicitly uses mesh networks. IoT connectivity to cloud and edge computing is in vogue. A Wireless Mesh Network (WMN) is a multi-hop and distributed wireless network with mesh routers and mesh clients. Data originating from mesh clients are forwarded to destinations through mesh routers. In IoT Mesh networks, mesh clients are IoT devices. The crucial security issue with these networks is the lack of a trusted third party for validation. However, trust between nodes is required for the proper functioning of the network. WMNs are particularly vulnerable as they rely upon cooperative forwarding. In this research work, a secure and sustainable novel trust mechanism framework is proposed. This framework identifies the malicious nodes in WMNs and improves the nodes' cooperation. The proposed framework or model differentiates between legitimate and malicious nodes using direct trust and indirect trust. Direct trust is computed based on the packet-forwarding behavior of a node. Mesh routers have multi-radios, so the promiscuous mode may not work. A new two-hop mechanism is proposed to observe the neighbors' packet forwarding behavior. Indirect trust is computed by aggregating the recommendations using the weighted D-S theory, where weight is computed using a novel similarity mechanism that correlates the recommendations received from different neighbors. Dynamic weight computation calculates the overall trust by using several interactions. We present the evaluations to show the effectiveness of the proposed approach in the presence of packet drop/modification attacks, bad-mouthing attacks, on-off attacks, and collusion attacks by using the ns-2 simulator.