Intrusion Detection System in Manets
M.Durairaj1, S.Dilipkumar2
1Dilipkumar S*, Department of Computer Science & Engineering, Bharathidasan University, Trichy India.
2Dr. M.Durairaj, Department of CSE, Bharathidasan University, Trichy India.
Manuscript received on November 17., 2019. | Revised Manuscript received on November 24 2019. | Manuscript published on 30 November, 2019. | PP: 12801-12803 | Volume-8 Issue-4, November 2019. | Retrieval Number: D6878118419/2019©BEIESP | DOI: 10.35940/ijrte.D6878.118419
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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: One of the most challenging issue nowadays is providing security on MANET architecture. The key issue in MANET is the design of intrusion detection system, that is able to detect attacks in a rapid manner .Traditional methods like genetic algorithms, fuzzy logic, game theory techniques are helpful in designing of IDs. However, these techniques have a limitation on the effects of prevention techniques in general and they are designed for a set of known attacks. These techniques are also tends to increase the false positive ratio, detection rate is low and values of ROC characteristics due to training of feature set of attack patterns . The techniques also failed to detect any new type of attacks by any existing methods. This paper focuses on designing of intrusion detection system based on hybrid approach that effectively able to detect any type of attacks using Evolutionary algorithm techniques.
Keywords: Intrusion Detection System, Attacks, Evolutionary Algorithms, Machine Learning Algorithms.
Scope of the Article: Machine Learning .