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Article type: Research Article
Authors: Vijaya Karthik, S.V.; * | Arputha Vijaya Selvi, J.
Affiliations: Department of ECE, Kings College of Engineering, Pudukkottai, Tamilnadu, India
Correspondence: [*] Corresponding author. S.V. Vijaya Karthik, Department of ECE, Kings College of Engineering, Pudukkottai, Tamilnadu, India. E-mail: [email protected].
Abstract: Information Centric Network (ICN) is a newer technology in handling web content distribution that has recently emerged in order to tackle the risk of data security. For handling content distribution, ICN provides data security via a name-based approach. Named Data Networking (NDN) is an ongoing ICN realisation that was incorporated recently. Named Data Networking (NDN) has recently grown in popularity and significance as a new internet design that solves certain limitations in traditional internet communications. NDN is perfectly adapted for the Internet of Things (IoT), which is today dominated by huge, and emerging applications. In this work, we propose an IoT enabled hybrid cluster-based routing protocol with mitigation of content poisoning attack for information-centric Wireless Sensor Network (WSN)-NDN. In this method, hybrid K-medoids clustering is used with African Buffalo Optimization Algorithm (ABOA), which is to find an optimal shortest path between the cluster heads, and light weight encryption. It is developed by using Hyperelliptic Curve Cryptography (HCC) to mitigate content poisoning. Our proposed system has effective data security as it has encrypted data in the cluster head. The smart health care monitoring system has been used for our proposed method. The proposed method has been subjected to extensive analysis by comparing with other existing methods that should improve performance justified in terms of several metrics by introducing the malicious nodes (10%, 20%, and 30%).
Keywords: Named data network, clustering algorithm, content poisoning, african buffalo optimization, hyperelliptic curve cryptography
DOI: 10.3233/JIFS-212674
Journal: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 2891-2905, 2022
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