Efficient Detection of Reactive Jamming Attacks in IoT Networks: A Collaborative Approach

Abstract

According to its wide range of domain applications, the Internet of Things, also known as the IoT, has attracted a lot of attention recently. With the rapid growth of IoT, security and privacy have become more critical and difficult to manage. Reactive jamming is a dangerous threat that may disrupt communication by providing inconsistent data. There are various approaches to solving this problem that propose distributed solutions. However, there are persistent issues, such as energy overheads and traffic delays. Therefore, this paper proposes a lightweight yet efficient method to detect reactive jamming attacks in IoT networks. It proposes the collaborative detection of the reactive jamming attack technique (CDRA) to detect reactive jamming attacks. In the proposed architecture, the nodes work collaboratively. Each node maintains neighborhood information by monitoring its behavior based on two metrics: the packet forwarding ratio (PFR) and the received signal strength indication (RSSI). The findings are compared to the most advanced, utilizing specific performance criteria (e.g., consumption of energy and traffic latency) using the Cooja simulator with varied traffic intervals, inappropriate node numbers, authentic conditions, and randomized mobility. The results show that the proposed approach outperformed the state of the art by consuming less energy and minimizing traffic delays. The detection time is also minimized. The result proves 3% reduced energy under varying traffic intervals and malicious nodes. It consumes 17% energy, which is 5% lower than the existing approach. It also reduces delay by 10% when compared to the existing approach.