Survey of Techniques for Mitigating Reactive Jamming Attacks in Internet of Things Networks
Enos Letsoalo, Tshimangadzo Tshilongamulendze, Deon Du Plessis · 2025
Internet of Things (IoT) networks benefits a variety of applications including smart cities, smart homes, intelligent transportation, smart agriculture, monitoring, surveillance, etc. The security challenges associated with IoT networks have been widely studied in the literature. This research paper is aimed at reviewing the existing research studies on IoT networks reactive jamming attacks, challenges, and mitigation. This paper examined the research studies published between 2019 and 2024 within the popular electronic digital libraries. The outcomes of this research paper reported three major IoT network performance issues namely: power consumption of IoT devices, transmission delays, and packet delivery ratio. The results showed that the existing mitigation methods can be categorized as machine learning based, deception-based, statistical-based, radio frequency based, and game theorybased. The results shows that most methods can detect reactive jamming attacks with accuracy. However, the methods still require additional infrastructure, encryption systems, and prolonged training due to large datasets leading to computational overhead and transmission delays. Furthermore, the methods are unable to provide better defence response to reactive jamming attacks. The outcomes underline considerable opportunities for continued investigation and improvement within this area