Visible to the public An Enhanced Approach for Attack Detection in VANETs Using Adaptive Neuro-Fuzzy System

TitleAn Enhanced Approach for Attack Detection in VANETs Using Adaptive Neuro-Fuzzy System
Publication TypeConference Paper
Year of Publication2019
AuthorsKaur, Jasleen, Singh, Tejpreet, Lakhwani, Kamlesh
Conference Name2019 International Conference on Automation, Computational and Technology Management (ICACTM)
Date Publishedapr
Keywordsadaptive neuro-fuzzy system, attack detection, compositionality, end to end delay, fuzzy neural nets, information dispersal approach, MANET Attack Detection, Metrics, mobile ad hoc network, mobile ad hoc networks, packet drop ratio, Protocols, pubcrawl, QoS, quality of service, resilience, Resiliency, Routing, routing attacks, security, telecommunication computing, temporary network, Throughput, VANETs, vehicle-to-vehicle availability, vehicular ad hoc networks
AbstractVehicular Ad-hoc Networks (VANETs) are generally acknowledged as an extraordinary sort of Mobile Ad hoc Network (MANET). VANETs have seen enormous development in a decade ago, giving a tremendous scope of employments in both military and in addition non-military personnel exercises. The temporary network in the vehicles can likewise build the driver's capability on the road. In this paper, an effective information dispersal approach is proposed which enhances the vehicle-to-vehicle availability as well as enhances the QoS between the source and the goal. The viability of the proposed approach is shown with regards to the noteworthy gets accomplished in the parameters in particular, end to end delay, packet drop ratio, average download delay and throughput in comparison with the existing approaches.
Citation Keykaur_enhanced_2019