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A novel and effective image encryption algorithm based on chaos and DNA encoding

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Abstract

In this paper, we proposed a novel and effective image encryption algorithm based on Chaos and DNA encoding rules. Piecewise Linear Chaotic Map (PWLCM) and Logistic Map are applied to generate all parameters the presented algorithm needs and DNA encoding technology functions as an auxiliary tool. The proposed algorithm consists of these parts: firstly, use PWLCM to produce a key image, whose pixels are generated by Chaos; Secondly, encode the plain image and the key image with DNA rules by rows respectively and different rows are encoded according to various rules decided by logistic map; After that, employ encoded key image to conduct DNA operations with the encoded plain image row by row to obtain an intermediate image and the specific operation executed every row is chosen by logistic map; Then, decode the intermediate image as the plain image of next step. Finally, repeat steps above by columns again to get the ultimate cipher image. The experiment results and analysis indicate that the proposed algorithm is capable of withstanding typical attacks and has good character of security.

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Acknowledgments

This research is supported by the National Natural Science Foundation of China (Nos: 61370145, 61173183, and 60973152), the Doctoral Program Foundation of Institution of Higher Education of China (No: 20070141014), Program for Liaoning Excellent Talents in University (No: LR2012003), the National Natural Science Foundation of Liaoning province (No: 20082165) and the Fundamental Research Funds for the Central Universities (No: DUT12JB06).

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Authors and Affiliations

  1. Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024, China

    Xingyuan Wang & Chuanming Liu

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  1. Xingyuan Wang
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  2. Chuanming Liu
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Correspondence to Xingyuan Wang.

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Wang, X., Liu, C. A novel and effective image encryption algorithm based on chaos and DNA encoding. Multimed Tools Appl 76, 6229–6245 (2017). https://doi.org/10.1007/s11042-016-3311-8

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  • DOI: https://doi.org/10.1007/s11042-016-3311-8

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