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Adaptive Color Image Encryption Scheme Based on Multiple Distinct Chaotic Maps and DNA Computing

Author

Listed:
  • Shaista Mansoor

    (Department of Electronics and Instrumentation Technology, University of Kashmir, Srinagar 190006, India)

  • Parsa Sarosh

    (Department of Electronics and Instrumentation Technology, University of Kashmir, Srinagar 190006, India)

  • Shabir A. Parah

    (Department of Electronics and Instrumentation Technology, University of Kashmir, Srinagar 190006, India)

  • Habib Ullah

    (Department of Data Science, Norwegian University of Life Sciences (NMBU), 1433 Ås, Norway
    Department of Industrial Economics, Norwegian University of Life Sciences (NMBU), 1433 Ås, Norway)

  • Mohammad Hijji

    (Faculty of Computers and Information Technology (FCIT), University of Tabuk, Tabuk 47711, Saudi Arabia
    Industrial Innovation and Robotic Centre (IIRC), University of Tabuk, Tabuk 47711, Saudi Arabia)

  • Khan Muhammad

    (Visual Analytics for Knowledge Laboratory (VIS2KNOW Lab), Department of Applied Artificial Intelligence, School of Convergence, College of Computing and Informatics, Sungkyunkwan University, Seoul 03063, Korea)

Abstract

In this paper, we propose an adaptive encryption scheme for color images using Multiple Distinct Chaotic Maps (MDCM) and DNA computing. We have chosen three distinct chaotic maps, including a 2D-Henon map, a Tent map, and a Logistic map, to separately encrypt the red, green, and blue channels of the original image. The proposed scheme adaptively modifies the parameters of the maps, utilizing various statistical characteristics such as mean, variance, and median of the image to be encrypted. Thus, whenever there is a change in the plain image, the secret keys also change. This makes the proposed scheme robust against the chosen and known plaintext attacks. DNA encoding has also been used to add another layer of security. The experimental analysis of the proposed scheme shows that the average value of entropy is approximately eight, the Number of Pixels Change Rate (NPCR) and Unified Average Changing Intensity (UACI) are 99.61% and 33%, respectively, and correlation coefficients close to zero, making the scheme not only reliable but also resilient against many attacks. Moreover, the use of low-dimensional maps reduces the computational costs of the scheme to a large extent.

Suggested Citation

  • Shaista Mansoor & Parsa Sarosh & Shabir A. Parah & Habib Ullah & Mohammad Hijji & Khan Muhammad, 2022. "Adaptive Color Image Encryption Scheme Based on Multiple Distinct Chaotic Maps and DNA Computing," Mathematics, MDPI, vol. 10(12), pages 1-20, June.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:12:p:2004-:d:835854
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    References listed on IDEAS

    as
    1. Nardo, Lucas G. & Nepomuceno, Erivelton G. & Arias-Garcia, Janier & Butusov, Denis N., 2019. "Image encryption using finite-precision error," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 69-78.
    2. Hongyan Zang & Mengdan Tai & Xinyuan Wei, 2022. "Image Encryption Schemes Based on a Class of Uniformly Distributed Chaotic Systems," Mathematics, MDPI, vol. 10(7), pages 1-21, March.
    3. Xiangjun Wu & Yang Li & Jürgen Kurths, 2015. "A New Color Image Encryption Scheme Using CML and a Fractional-Order Chaotic System," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-28, March.
    4. Alghafis, Abdullah & Firdousi, Faiza & Khan, Majid & Batool, Syeda Iram & Amin, Muhammad, 2020. "An efficient image encryption scheme based on chaotic and Deoxyribonucleic acid sequencing," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 177(C), pages 441-466.
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    Cited by:

    1. Zou, Chengye & Wang, Lin, 2023. "A visual DNA compilation of Rössler system and its application in color image encryption," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    2. Hemalatha Mahalingam & Padmapriya Velupillai Meikandan & Karuppuswamy Thenmozhi & Kawthar Mostafa Moria & Chandrasekaran Lakshmi & Nithya Chidambaram & Rengarajan Amirtharajan, 2023. "Neural Attractor-Based Adaptive Key Generator with DNA-Coded Security and Privacy Framework for Multimedia Data in Cloud Environments," Mathematics, MDPI, vol. 11(8), pages 1-23, April.

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