Penalty Based Reliable Cooperative Intrusion Detection System for Mobile Adhoc Network Environment
Adilakshmi Yannam1, G.V.S.N.R.V.Prasad2
1RAdilakshmi Yannam *, Research Scholar, CSE Department, JNTUK, Kakinada, India.
2Dr. G. V.S.N.R. V. Prasad, CSE Gudlavalleru Engineering College, Gudlavalleru, India.
Manuscript received on November 12, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on 30 November, 2019. | PP: 8581-8588 | Volume-8 Issue-4, November 2019. | Retrieval Number: D6742118419/2019©BEIESP | DOI: 10.35940/ijrte.D6742.118419
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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: Intrusion detection is the process of finding the malicious behaviour happening in the network to enhance the network performance. This is the most focused research by various researchers to ensure the secured network to the users for increasing their satisfaction level. This is achieved in the previous work by introducing the method namely Cooperative intrusion detection system (CIDS). However this research method doesn’t focus on selfish node presence which might affect the overall intrusion detection process. There is a chance of that monitoring node also can act as selfish node. This is resolved in the proposed work by introducing the method namely Penalty based Reliable Cooperative Intrusion Detection System (PR-CIDS). In this work, initially monitoring nodes are selected optimally by using modified artificial bee colony algorithm through which intrusion detection will be performed. Here intrusion detection is performed based on variation in the forwarded traffic. In order to avoid the selfish node presence, in this work unique secret keys are generated for each monitoring node by using which intrusion decision will be encrypted and then send to the third party node. Here third party node will authenticate the node and then will utilize the intrusion information to make the final decision. Third party node plays more important role in making the intrusion decision. Thus the most suitable third party node is selected by using Hybrid Ant colony with Genetic method. Based on this decision, penalty will be assigned to the selfish monitoring nodes. The overall evaluation of the research work is done in the NS2 simulation environment to prove their performance improvement.
Keywords: Penalty, Intrusion Decision, Cooperative Decision Making, Third Party Node, Monitoring Nodes.
Scope of the Article: Decision Making.