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An artificial immune system‐based algorithm for selfish node detection in Mobile Ad Hoc Networks (MANETs)

Authors :
Gowtham, M. S.
Vigenesh, M.
Ramkumar, M.
Source :
Transactions on Emerging Telecommunications Technologies; February 2024, Vol. 35 Issue: 2
Publication Year :
2024

Abstract

The Mobile Ad Hoc Network (MANET) depending on dynamic distributed topology presents several challenges such as decentralized infrastructure. In MANET, each node act as a host as well as a router to exchange packet. From Source to destination, the MANET nodes offer the ability of transmission to send, receive, and route traffic. Moreover, the presence of selfish nodes or malicious nodes in MANETs significantly degrades network performance. Identifying and isolating such nodes poses a formidable challenge. Consequently, this research introduces a security model founded on the principles of an Artificial Immune System (AIS) to detect and defend against Selfish Node (SN) attacks. This research work employs the principles of AIS to categorize a node's behavioral state based on the Mature Context Immune Antigen Rate (MCIAR). Subsequently, a hybrid protocol named Reliable History‐dependent Resource Conscious Clustered and Defensive AODV (RRCC‐DAODV) is introduced to detect Selfish Nodes (SNs) and counteract their attacks. Within the RRCC algorithm, the identification of selfish nodes relies on both Trust Value (TV) and Residual Energy (RE). Additionally, the proposed DAODV protocol incorporates the V‐detector algorithm to enhance defense mechanisms against potential attacks. The simulation of the proposed model is carried out in NS3. The proposed mechanism achieves a detection ratio of 94.05%. The simulation outcomes demonstrate the excellence of the implemented system. This superiority is observed when compared to other standard protocols, as indicated by the parameters of throughput, residual energy, packet delivery ratio, and delay. This research introduces a security model based on the principles of an Artificial Immune System (AIS) to detect and defend against attacks from selfish nodes.The study utilizes AIS principles to categorize a node's behavioral state using the Mature Context Immune Antigen Rate (MCIAR). Subsequently, a hybrid protocol named Reliable History‐dependent Resource Conscious Clustered and Defensive AODV (RRCC‐DAODV) is introduced to detect Selfish Nodes (SNs) and counteracttheir attacks. Within the RRCC algorithm, the identification of selfish nodesis based on both Trust Value (TV) and Residual Energy (RE). The proposed DAODV protocol incorporates the V‐detector algorithm to enhance defense mechanisms against potential attacks.

Details

Language :
English
ISSN :
21615748 and 21613915
Volume :
35
Issue :
2
Database :
Supplemental Index
Journal :
Transactions on Emerging Telecommunications Technologies
Publication Type :
Periodical
Accession number :
ejs65507010
Full Text :
https://doi.org/10.1002/ett.4938