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Modified Adhoc On-Demand Distance Vector for Trust Evaluation And Attack Detection

S. Soundararajan1,*, B. R. Tapas Bapu2, C. Kotteeswaran1, S. Venkatasubramanian3, P. J. Sathish Kumar4, Ahmed Mudassar Ali2

1 Anna University, Chennai, 600025, Tamil Nadu, India
2 S.A. Engineering College, Veeraraghavap, Chennai, 600077, Tamil Nadu, India
3 Saranathan College of Engineering, Trichy, 620019, Tamil Nadu, India
4 Panimalar Engineering College, Chennai, 600069, Tamilnadu, India

* Corresponding Author: S. Soundararajan. Email: email

Intelligent Automation & Soft Computing 2023, 36(2), 1227-1240.


Recently, Wireless Sensor Network (WSN) becomes most potential technologies for providing improved services to several data gathering and tracking applications. Because of the wireless medium, multi-hop communication, absence of physical protectivity, and accumulated traffic, WSN is highly vulnerable to security concerns. Therefore, this study explores a specific type of DoS attack identified as a selective forwarding attack where the misbehaving node in the network drops packet on a selective basis. It is challenging to determine if packet loss is caused by a collision in the medium access path, poor channel quality, or a selective forwarding assault. Identifying misbehaving nodes at the earliest opportunity is an acceptable solution for performing secure routing in such networks. As a result, in this study effort, we present a unique Modified Ad Hoc On-Demand Distance Vector (AODV) Routing protocol depending upon the One time password (OTP) method that employs the RSA algorithm. Finally, a trust evaluation process determines which approach is the most optimal. According to the simulation findings of the suggested routing protocol and comparison with existing routing protocols provided in this article, the proposed work is both efficient and cost-effective.


Cite This Article

S. Soundararajan, B. R. Tapas Bapu, C. Kotteeswaran, S. Venkatasubramanian, P. J. Sathish Kumar et al., "Modified adhoc on-demand distance vector for trust evaluation and attack detection," Intelligent Automation & Soft Computing, vol. 36, no.2, pp. 1227–1240, 2023.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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