Visible to the public Development of an Intrusion Detection System Prototype in Mobile Ad Hoc Networks Based on Machine Learning Methods

TitleDevelopment of an Intrusion Detection System Prototype in Mobile Ad Hoc Networks Based on Machine Learning Methods
Publication TypeConference Paper
Year of Publication2022
AuthorsLegashev, Leonid, Grishina, Luybov
Conference Name2022 International Russian Automation Conference (RusAutoCon)
KeywordsAd Hoc Network Security, Blackhole attack, composability, DDoS Attack, Intrusion detection, intrusion detection system, machine learning, Measurement, Metrics, mobile ad hoc network, Network topology, Prototypes, pubcrawl, resilience, Resiliency, telecommunication traffic, Throughput
AbstractWireless ad hoc networks are characterized by dynamic topology and high node mobility. Network attacks on wireless ad hoc networks can significantly reduce performance metrics, such as the packet delivery ratio from the source to the destination node, overhead, throughput, etc. The article presents an experimental study of an intrusion detection system prototype in mobile ad hoc networks based on machine learning. The experiment is carried out in a MANET segment of 50 nodes, the detection and prevention of DDoS and cooperative blackhole attacks are investigated. The dependencies of features on the type of network traffic and the dependence of performance metrics on the speed of mobile nodes in the network are investigated. The conducted experimental studies show the effectiveness of an intrusion detection system prototype on simulated data.
DOI10.1109/RusAutoCon54946.2022.9896238
Citation Keylegashev_development_2022