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An efficient hybrid encryption model based on deep convolutional neural networks, deoxyribonucleic acid computing and chaotic system

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Abstract

In this research, we present a substantial image encryption system constructed on deep convolutional neural networks for key generation to reduce processing power, complexity, and time consumption, as well as a creative method of DNA sequence operations and scrambling to encrypt digital images. A two-dimensional Logistic map is used to perform a chaotic scrambling. The results of the experiments, as well as security analysis such as statistical, differential, and key space analysis, demonstrated that the suggested method may achieve a high level of security while remaining efficient. With UACI and NPCR of 33.4 and 99.6, respectively, the method achieves an average entropy of 7.999 and a near-zero correlation. The algorithm’s efficiency is also evaluated to the state of the art in encryption techniques.

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Authors and Affiliations

  1. Department of Electrical Engineering, Institute of Space Technology, Islamabad, Pakistan

    Nazish Iqbal & Khurram Khurshid

  2. Department of Applied Mathematics & Statistics, Institute of Space Technology, Islamabad, Pakistan

    Majid Khan

  3. Mathematics Program, Department of Mathematics, Statistics and Physics, College of Arts and Sciences, Qatar University, Doha, 2713, Qatar

    Iqtadar Hussain

  4. Statistical Consulting Unit, Department of Mathematics, Statistics and Physics, College of Arts and Science, Qatar University, Doha, Qatar

    Iqtadar Hussain

Authors
  1. Nazish Iqbal
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  2. Majid Khan
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  3. Khurram Khurshid
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  4. Iqtadar Hussain
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Correspondence to Majid Khan.

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Iqbal, N., Khan, M., Khurshid, K. et al. An efficient hybrid encryption model based on deep convolutional neural networks, deoxyribonucleic acid computing and chaotic system. Multimed Tools Appl 82, 13881–13903 (2023). https://doi.org/10.1007/s11042-022-13910-z

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  • DOI: https://doi.org/10.1007/s11042-022-13910-z

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