Proceedings of The International Conference on Emerging Trends in Artificial Intelligence and Smart Systems, THEETAS 2022, 16-17 April 2022, Jabalpur, India

Research Article

Optimizing Fuzzy Adaptive Based Metaheuristics ABC to Detect Malicious Node to improve the performance of WSN

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  • @INPROCEEDINGS{10.4108/eai.16-4-2022.2318174,
        author={Virendra  Tiwari and Akhilesh A.  Waoo},
        title={Optimizing Fuzzy Adaptive Based Metaheuristics ABC to Detect Malicious Node to improve the performance of WSN},
        proceedings={Proceedings of The International Conference on Emerging Trends in Artificial Intelligence and Smart Systems, THEETAS 2022, 16-17 April 2022, Jabalpur, India},
        publisher={EAI},
        proceedings_a={THEETAS},
        year={2022},
        month={6},
        keywords={wireless sensor network (wsn) clustering artificial bee colony (abc) sinkhole attacks swarm intelligence security},
        doi={10.4108/eai.16-4-2022.2318174}
    }
    
  • Virendra Tiwari
    Akhilesh A. Waoo
    Year: 2022
    Optimizing Fuzzy Adaptive Based Metaheuristics ABC to Detect Malicious Node to improve the performance of WSN
    THEETAS
    EAI
    DOI: 10.4108/eai.16-4-2022.2318174
Virendra Tiwari1,*, Akhilesh A. Waoo1
  • 1: Department of CSE, AKS University, Satna, Madhya Pradesh
*Contact email: virentiwari@gmail.com

Abstract

The Wireless Sensor Networks comprises a set of sensors situated at different locations, usually employed for the gathering of data and tracking applications like monitoring the movement of autonomous nodes in both static and dynamic environments. However, the design of WSN has some the vulnerabilities mainly; its security problems nowadays are found hot research topics in many applications by the researchers. To prevent sinkhole attacks, this paper is doing some research on it and will try to deploy an enhancing and Optimized Artificial Bee Colony algorithm based on fuzzy logic to improve sinkhole detection via packet delivery rate, packet drop, energy exchange, and throughput in a wireless sensor network. Lastly, a simulation using NS2 is performed to evaluate the effectiveness and accuracy by showing initial results and the expected outcome of the proposed model, and the executed simulation result shows that the proposed model could work to some extent.