Open AccessSINKHOLE ATTACK DETECTION IN MANET USING SWARM INTELLIGENCE TECHNIQUES
Author(s) -
Laxmi Laxmi,
Rashmi Popli
Publication year - 2020
Publication title -
international journal of engineering applied science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-2143
DOI - 10.33564/ijeast.2020.v05i04.021
Subject(s) - sinkhole , mobile ad hoc network , computer science , swarm intelligence , swarm behaviour , computer security , artificial intelligence , geography , machine learning , archaeology , particle swarm optimization , karst , network packet
Mobile Adhoc Network (MANET) is multi-hop remote system of self-governing versatile nodes with no preset framework where each node can move toward any path to play a task of router. In a mobile ad-hoc network (MANET), there is a short-lived network setup by unbounded nodes, which move anywhere and communicate within the absence of centralized network. Sinkhole attack may be a network layer attack, which affect the overall network. The information is attracted by sinkhole node from the neighboring node and after that, it counterfeits the steering data that makes the local area network know its way on specific node. Therefore, sinkhole tries that all the data passed through this node. Therefore, it modifies the packet information or drops the packet silently. This paper includes the optimization of route for sinkhole attack using Ant colony optimization and detects the sinkhole attack by using the Enhanced Particle swarm optimization technique. This paper also uses the MD5 (Message Digest) Algorithm for hashing and voting method for ranking the nodes. Keywords— MANET, ACO, EPSO, MD5, RREQ, RREP