A Blockchain Based Framework for Reputation Management and Node Misbehaviour Detection in Wireless Sensor Networks

Abstract

With the growth of smart applications such as smart cities and smart farming, the importance of Wireless Sensor Networks (WSNs) is gradually being realized by many industrial enterprises. In particular, WSNs have shown enormous potential for being an interesting research area and in this decade, it is expected to grow manifold both in terms of applications as well as business revenues. WSNs consist of resourceconstrained devices which are present in an open and unsecured environment, and this makes them vulnerable to both internal as well as external attacks. Internal attacks can affect the network’s performance by increased energy consumption and introducing transmission delays. Consequently, this represents a critical security challenge for the deployment of WSNs. Many researchers have proposed solutions based on trust management systems that proves to be an efficient way for detecting such attacks by enhancing trust relationships and data routing reliability. In this thesis, we extend the trust management system to include a distributed consensus mechanism based on blockchain which validates data packets originating from various source nodes. Additionally, a new algorithm is developed to estimate a node’s reputation based on its historical energy consumption data. Reputation and trust are both crucial factors that characterize malicious behaviour in the network. We have evaluated our proposed work with another existing trust model named Belief-based Trust Evaluation Mechanism (BTEM) and compared our results in terms of performance metrics after performing various simulation runs. The results show that there is a significant improvement in the detection rate and accuracy. Furthermore, we have shown that our framework fulfils important security requirements such as integrity, authenticity and confidentiality by analyzing it for various security attacks. Additionally, based on our analysis and findings, our framework can be used to detect any malicious activity in the routing process of a wireless sensor network.