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Improved Homomorphic Encryption with Optimal Key Generation Technique for VANETs

G. Tamilarasi1,*, K. Rajiv Gandhi2, V. Palanisamy1

1 Department of Computer Applications, Alagappa University, Karaikudi, 630004, Tamilnadu, India
2 Department of Computer Science, Alagappa University Model Constituent College, Paramakkudi, 623707, Tamilnadu, India

* Corresponding Author: G. Tamilarasi. Email: email

Intelligent Automation & Soft Computing 2022, 33(2), 1273-1288. https://doi.org/10.32604/iasc.2022.024687

Abstract

In recent years, vehicle ad hoc networks (VANETs) have garnered considerable interest in the field of intelligent transportation systems (ITS) due to the added safety and preventive measures for drivers and passengers. Regardless of the benefits provided by VANET, it confronts various challenges, most notably in terms of user/message security and privacy. Due to the decentralised nature of VANET and its changeable topologies, it is difficult to detect rogue or malfunctioning nodes or users. Using an improved grasshopper optimization algorithm (IGOA-PHE) technique in VANETs, this research develops a new privacy-preserving partly homomorphic encryption with optimal key generation. The suggested IGOA-PHE approach is intended to provide privacy and security in VANETs. The proposed IGOA-PHE technique consists of two stages: an ElGamal public key cryptosystem (EGPKC) for PHE and an optimised key generation procedure based on IGOA. To enhance the security of the EGPKC approach, the keys are selected ideally utilising the IGOA. Additionally, the IGOA is derived by using Gaussian mutation (GM) and Levy flights ideas. The experimental investigation of the proposed IGOA-PHE approach is extensive. The resulting results demonstrated that the provided IGOA-PHE technique outperformed recent state-of-the-art methods.

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Cite This Article

G. Tamilarasi, K. Rajiv Gandhi and V. Palanisamy, "Improved homomorphic encryption with optimal key generation technique for vanets," Intelligent Automation & Soft Computing, vol. 33, no.2, pp. 1273–1288, 2022.



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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