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Article type: Research Article
Authors: Alli, P.a; * | Dinesh Peter, J.b
Affiliations: [a] Department of Computer Science and Engineering, Velammal College of Engineering and Technology, Madurai, India | [b] Department of Computer Science and Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India
Correspondence: [*] Corresponding author. P. Alli, Department of Computer Science and Engineering, Velammal College of Engineering and Technology, Madurai, India. E-mail: [email protected].
Abstract: The day-to-day progress in communication plays a vital role in transmitting millions and trillions of data through the unsecured network channels. It creates a way where the user’s data becomes the victim of various security threats. Among those users’ data, images act as primary data, and its encryption security methodologies are fascinating. The conventional encryption techniques don’t work well against the various other hidden security threats but require substantial computational time and cost with poor permutation performance. Hence to deal with this, an auto-encoder induced DNA (Deoxyribonucleic acid) sequence via chaotic image encryption framework is designed in our proposed work. It integrates the properties of DNA encoding and the chaotic maps to handle the data losses effectively and resist several attacks such as statistical attacks, chosen-plaintext attacks, etc. Moreover, an auto-encoder is used to control the data noises, thereby ensuring a better encryption performance. Here, the auto-encoder is activated to generate a permuted image with less time complexity and noise. A secret key is then initialized with the aid of SHA-256. Finally, image encryption and decryption are achieved, followed by the successful transmission of data over a digital network. The performance of the proposed work is analyzed with varied metrics to strengthen its efficiency over the prior techniques.
Keywords: Permuted image, SHA-256, DNA computing sequence, stacked auto-encoder, chaos based image encryption
DOI: 10.3233/JIFS-201224
Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 181-198, 2021
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