Title | Mitigating Routing Misbehavior using Blockchain-Based Distributed Reputation Management System for IoT Networks |
Publication Type | Conference Paper |
Year of Publication | 2019 |
Authors | Li, Min, Tang, Helen, Wang, Xianbin |
Conference Name | 2019 IEEE International Conference on Communications Workshops (ICC Workshops) |
Keywords | attack detection, blockchain technique, blockchain-based reputation management system, centralized router RM systems, computer network management, computer network reliability, computer network security, cryptocurrencies, data forwarding services, decentralized database, distributed blockchain-based RM system, distributed consensus mechanism, Distributed databases, inherent decentralized consensus mechanism, Internet of Thing devices, Internet of Things, IoT networks, malicious misbehaving routers, Metrics, one-point failure risk, pubcrawl, reputation calculation mechanism, resilience, Resiliency, Router Systems Security, routing misbehavior mitigation, system convergence performance, telecommunication network routing |
Abstract | With the rapid proliferation of Internet of Thing (IoT) devices, many security challenges could be introduced at low-end routers. Misbehaving routers affect the availability of the networks by dropping packets selectively and rejecting data forwarding services. Although existing Reputation Management (RM) systems are useful in identifying misbehaving routers, the centralized nature of the RM center has the risk of one-point failure. The emerging blockchain techniques, with the inherent decentralized consensus mechanism, provide a promising method to reduce this one-point failure risk. By adopting the distributed consensus mechanism, we propose a blockchain-based reputation management system in IoT networks to overcome the limitation of centralized router RM systems. The proposed solution utilizes the blockchain technique as a decentralized database to store router reports for calculating reputation of each router. With the proposed reputation calculation mechanism, the reliability of each router would be evaluated, and the malicious misbehaving routers with low reputations will be blacklisted and get isolated. More importantly, we develop an optimized group mining process for blockchain technique in order to improve the efficiency of block generation and reduce the resource consumption. The simulation results validate the distributed blockchain-based RM system in terms of attacks detection and system convergence performance, and the comparison result of the proposed group mining process with existing blockchain models illustrates the applicability and feasibility of the proposed works. |
DOI | 10.1109/ICCW.2019.8757083 |
Citation Key | li_mitigating_2019 |