Black Hole attack Detection using Fuzzy based Intrusion Detection Systems in MANET

Mobile Ad hoc NETworks (MANETs) are a new type of wireless communications that are operating in a highly dynamic and unpredictable environment. These networks are becoming increasingly popular and more essential to wireless communications in recent years due to their ease of deployment and growing popularity of mobile devices. A MANET is a group of wireless mobile nodes that are able to communicate with each other without using centralized administration or fixed infrastructure. Therefore, providing communications even in the absence of any fixed infrastructure or centralized administration, MANETs became an attractive technology for many applications. However, this flexibility brings new threats to security. The black hole attack is considered as one of the most affected kind on MANETs. In addition, the traditional method of protecting wired networks or wireless networks with infrastructure does not apply directly to MANETs. Since prevention techniques are never enough, the use of an Intrusion Detection System (IDS) has a major importance in the MANET protection. In this paper, a new scheme has been proposed by using an Adaptive Neuro Fuzzy Inference System (ANFIS) and Particle Swarm Optimization (PSO) for mobile ad hoc networks to detect the black hole attack. (C) 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the Conference Program Chairs.