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Genetic and chaotic signatures in offspring – an encrypted generation of image family

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Abstract

With the rapid escalation of information technology and the internet, the digital image has turned out to be a vital medium for communication. Hence, there is an increasing demand to protect these digital images as they are transmitted over the insecure medium such as the Internet. This paper proposes the Genetic Algorithm influenced image encryption scheme. Both crossover and mutation operations were performed to enhance the statistical measures of the grayscale cipher images. Intra-pixel bit manipulation improved the diffusion property during mutation. Crossover accomplished the generation of offspring with the confluence of image intensities and keys. The chaotic Logistic and Tent maps provided improvement in keyspace through their role in the generation of initial seeds. Noticeably, the initial seeds were generated from the features of input image such as minimum & maximum number of occurrences of intensity and minimum & maximum intensity levels. In this regard, every image will accompany a unique key sequence as a session key which needs to be shared with the intended receiver for the distortion-free recovery of original images. Besides, the multi-point genetic crossover was employed for diffusion which resulted in the production of a couple of offspring. The Fitness test which decides the number of generations was executed by performing correlation and entropy analyses at a threshold of 0.01 and 7.99 for the former and later respectively. The investigational consequences authenticate that the proposed scheme not only reveals simple and optimised encryption, it is also defending against various distinctive attacks. The proposed image security solutions can be incorporated in banking, medical insurances, e-healthcare, and e-governance sectors for document confidentiality and integrity checking mechanisms.

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Acknowledgments

Authors thank Department of Science & Technology, New Delhi for the FIST funding (SR/FST/ET-II/2018/221). Also, Authors wish to thank the Intrusion Detection Lab at School of Electrical & Electronics Engineering, SASTRA Deemed University for providing infrastructural support to carry out this research work and also wish to thank Dr. R. Sundraraman, Sridevi Arumugam, Dhivya Ravichandran, Sivaraman Rethinam and Information Security Research Group / SEEE/ SASTRA Deemed University for their Time and Linguistic support.

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Authors and Affiliations

  1. School of Electrical & Electronics Engineering, SASTRA University, Thanjavur, 613 401, India

    C. Lakshmi, K. Thenmozhi, John Bosco Balaguru Rayappan & Rengarajan Amirtharajan

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  1. C. Lakshmi
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  2. K. Thenmozhi
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  4. Rengarajan Amirtharajan
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Correspondence to Rengarajan Amirtharajan.

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Lakshmi, C., Thenmozhi, K., Rayappan, J.B.B. et al. Genetic and chaotic signatures in offspring – an encrypted generation of image family. Multimed Tools Appl 80, 8581–8609 (2021). https://doi.org/10.1007/s11042-020-09978-0

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