A Gini Index-Based Countermeasure Against Sybil Attack in the Internet of Things

As an essential ingredient of Internet of Things (IoT), IPv6-based Low Power and Lossy Networks (LLNs) largely consisting of various resource-constrained devices are expeditiously proliferating and playing an important role in the realization of ubiquitous computing and communication infrastructure. In order to provide efficient and reliable communication between resource-constrained devices and connect them to the Internet, a novel routing protocol for LLNs, a.k.a. RPL, has been proposed. However, due to wide distribution, openness, and instinctive resource constraints of IoT devices, IoT and its applications become an ideal target for cyber attacks. Thus, investigating potential attacks against IoT-related routing protocol is a top priority to improve the security of the future IoT systems. In this paper, we propose a Gini index-based countermeasure to effectively detect and mitigate sybil attack in RPL-based LLNs, where the malicious node multicasts an excessive number of DODAG Information Solicitation (DIS) messages with different fictitious identities to cause the legitimate nodes to restart the Trickle algorithm frequently and broadcast a large number of DODAG Information Object (DIO) messages to quickly drain the limited energy resource of legitimate nodes. We conduct extensive simulation experiments for performance evaluation and comparison using OMNeT++, and the simulation results show that the proposed countermeasure can accurately detect and effectively mitigate sybil attack, indicating a viable approach against cyber attack in the Internet of Things.