Security Measure to Detect and Avoid Flooding Attacks using Multi-Agent System in MANETS

Security is considered as one of the major challenge when it comes to infrastructure less and self dependent network without any centralized control. The vulnerability of Adhoc Network makes it susceptible to external attacks like flooding of hello messages or propagating fake routing messages etc. Such attacks generates a variety of problems like disturbing the network by flooding messages that results in waste of battery which is a vital resource to maintain the life span of the network. Most importantly cause agents to die when unable to reach destination due to fake routing messages causing a heavy loss on part of the nodes generating them to maintain the route knowledge.  The paper proposes a novel technique to identify the flooding attack and measure to overcome them using Multi-Agent system

Self Adaptive Intrusion Detection Technique Using Data Mining Concept in an Ad-hoc Network

AbstractThe Intrusion Detection System mainly adopted from the traditional Wired Network or Distributed Network cannot provide a satisfying solution to the increasing security threats in an Ad-Hoc Network. Adhoc-Network due to its typical infrastructure less technical background, implementing an effective security solution for it is extremely challenging. Moreover due to its vulnerable nature attackers consistently try new attack mechanism which generally goes undetected for the system that uses pattern matching to detect traces os intrusion behavior in the incoming data. The paper aims at providing IDS based on self learning technique where the system when comes across an unknown data pattern classifies it as an attack or non attack after comparing and considering its variation from an attack free scenario