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A Novel Approach for Image Encryption Using Zaslavskii Map and Arnold’s Cat Map

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Data Engineering and Intelligent Computing

Abstract

Recently, transformation of information is an emerging area of interest because of efficient Internet technology and faster communication medium. Nowadays, huge numbers of data transferred over many transferring mediums, out of which image is one of them. To maintain confidentiality and provide ownership of the data, we need to do any cryptographic technique like encryption. In this paper, we proposed a new cryptography technique for image encryption which is a combination of two different techniques for image encryption to increase the security of the data. The two different techniques are Zaslavskii map and Arnold’s cat map. Both combinedly used for encryption as well as decryption. In this work, we first encrypt the image using Zaslavskii method, and then again, that encrypted image re-encrypted using Arnold’s cat map to re-encrypt that, to get the required image using two times encryption. Then, in the reverse process, the final encrypted image undergoes first decryption using Arnold’s cat map, and that decrypted image further undergoes Zaslavskii decryption to get back the final derived image which should be like the original image. This proposed technique gives users more key values for better security and unpredictability, which shows good entropy value and good correlation value. The efficiency of image encryption techniques is verified by number of pixels change rate (NPCR) and unified average chaning intensity (UACI) which is used for any small change in pixels, along with entropy and correlation coefficient values.

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Ramakant Parida, R.N., Kumar Singh, B., Pradhan, C. (2021). A Novel Approach for Image Encryption Using Zaslavskii Map and Arnold’s Cat Map. In: Bhateja, V., Satapathy, S.C., Travieso-González, C.M., Aradhya, V.N.M. (eds) Data Engineering and Intelligent Computing. Advances in Intelligent Systems and Computing, vol 1407. Springer, Singapore. https://doi.org/10.1007/978-981-16-0171-2_26

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