Open Access

ARTICLE

Cryptographic Lightweight Encryption Algorithm with Dimensionality Reduction in Edge Computing

D. Jerusha^*, T. Jaya

CSI Institute of Technology, Nagercoil, India

* Corresponding Author: D. Jerusha. Email:

Computer Systems Science and Engineering 2022, 42(3), 1121-1132. https://doi.org/10.32604/csse.2022.022997

Received 25 August 2021; Accepted 29 September 2021; Issue published 08 February 2022

Abstract

Edge Computing is one of the radically evolving systems through generations as it is able to effectively meet the data saving standards of consumers, providers and the workers. Requisition for Edge Computing based items have been increasing tremendously. Apart from the advantages it holds, there remain lots of objections and restrictions, which hinders it from accomplishing the need of consumers all around the world. Some of the limitations are constraints on computing and hardware, functions and accessibility, remote administration and connectivity. There is also a backlog in security due to its inability to create a trust between devices involved in encryption and decryption. This is because security of data greatly depends upon faster encryption and decryption in order to transfer it. In addition, its devices are considerably exposed to side channel attacks, including Power Analysis attacks that are capable of overturning the process. Constrained space and the ability of it is one of the most challenging tasks. To prevail over from this issue we are proposing a Cryptographic Lightweight Encryption Algorithm with Dimensionality Reduction in Edge Computing. The t-Distributed Stochastic Neighbor Embedding is one of the efficient dimensionality reduction technique that greatly decreases the size of the non-linear data. The three dimensional image data obtained from the system, which are connected with it, are dimensionally reduced, and then lightweight encryption algorithm is employed. Hence, the security backlog can be solved effectively using this method.

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Keywords

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