Performance evaluation of a Fuzzy Logic-based IDS (FLIDS) technique for the Detection of Different Types of Jamming Attacks in IoT Networks
Michael Savva, Iacovos I. Ioannou, Vasos Vassiliou · 2023
This paper evaluates the effectiveness and performance of the Fuzzy Logic Intrusion Detection System (FLIDS) in recognising different types of jamming attacks. FLIDS is an intelligent and adaptive intrusion detection technique working in a distributed manner. The proposed approach feeds combinations of the Expected Transmission Count (ETX) & Retransmissions and Packets Drop per terminal (PDPT) & Retransmissions values into a Fuzzy inference system to generate the Jamming Index (JI). For the evaluation of this strategy, experiments are conducted in various Jamming scenarios with the usage of the Routing Protocol for Low-Power and Lossy Networks (RPL) targeting the identification of the jamming attack by utilising Contiki OS and Cooja Simulator tool. The review extends to five different jammers, two primary node placements, three sink positions, and two sets of input parameters. Simulation results indicate that Fuzzy Logic is a suitable technique for recognising different types of jamming attacks in various situations with high accuracy, low memory and fast execution time.