An Artificial Immune System Source-Based Immunization Approach with Centralized Monitoring and Tag Scaling for Misbehavior Detection in Mobile Ad-Hoc Networks
Nitin Tyagi1, Manas Kumar Mishra2
1Nitin Tyagi, Department of CEA, GLA University, Mathura (U.P), India.
2Manas Kumar Mishra, Department of CEA, GLA University, Mathura (U.P), India.
Manuscript received on 07 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 669-678 | Volume-8 Issue-5, March 2019 | Retrieval Number: E3318038519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In Mobile Ad-hoc network where node act as router. The network is helpless against for those nodes whose behavior is susceptible due to bad behavior. For detecting the bad behavior, misbehavior detection system is proposed. In proposed work it inculcates the concept of artificial immune system (AIS) to detect malicious node in mobile ad-hoc network. The goal is to build a system that, like its natural counterpart, automatically learns, and detects new misbehavior. In proposed work We used the concept of negative selection for provide the secure network and clonal selection is for detecting the malicious node based on Round Trip Time in mobile ad-hoc networks with centralized monitoring using the concept of tagging. Proposed strategy tried and confirmed for differing number of node and within the sight of varying percentage of malicious node.
Keyword: MANET, Problematic Node, Threshold, Scaling, Tagging.
Scope of the Article: Mobile Adhoc Network