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TPE-MM: Thumbnail preserving encryption scheme based on Markov model for JPEG images

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Abstract

Advances in mobile communication have enabled images to be shared more conveniently, and the consequent risk of privacy breaches has been increasingly emphasized. Previously, traditional image encryption algorithms were mostly adopted by individuals to encrypt plain images into noise-like meaningless cipher images. This type of algorithm provides security for image privacy protection but is unable to achieve usability in cloud platforms. Furthermore, existing image encryption algorithms only target the protection of lossless compression or non-compressed formats images (e.g., BMP, PNG, etc.), but neglect the encryption needs of JPEG format images. Since the latter has the benefits of less file storage and excellent visual quality, it has been widely applied in a variety of scenarios. Thus, a thumbnail preserving encryption (TPE) scheme based on Markov model (TPE-MM) for JPEG images is proposed to equilibrate security and availability. Specifically, an approximate sum-preserving encryption method (ASP-EM) in restricted range based on its features is proposed to preserve the plain thumbnail features to accomplish cipher image usability. Subsequently, an adaptive encryption method based on Markov model (AEM-MM) was proposed to improve the encryption effect of cipher images and retain the compression performance of JPEG images. Simulation experiments show that the cipher image has good visual quality, low expansion rate, and is resistant to outline attacks.

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Acknowledgements

All the authors are deeply grateful to the editors for smooth and fast handling of the manuscript. The authors would also like to thank the anonymous referees for their valuable suggestions to improve the quality of this paper. This work is supported by the National Natural Science Foundation of China (Grant Nos. 61802111, 61872125), the Science and Technology Project of Henan Province (Grant Nos. 232102210109, 232102210096), Key Scientific Research Projects of Colleges and Universities of Henan Province (Grant No. 24A520003), Pre-research Project of SongShan Laboratory (Grant No. YYJC012022011) and the Graduate Talent Program of Henan University (Grant Nos. SYLYC2022193 and SYLAL2023020).

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Authors and Affiliations

  1. School of Artificial Intelligence, Henan Engineering Research Center for Industrial Internet of Things, Henan University, Zhengzhou, 450046, China

    Xiuli Chai & Guoqiang Long

  2. School of Software, Intelligent Data Processing Engineering Research Center of Henan Province, Institute of Intelligent Network System, Henan University, Kaifeng, 475004, China

    Zhihua Gan

  3. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China

    Yushu Zhang

Authors
  1. Xiuli Chai
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  2. Guoqiang Long
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  3. Zhihua Gan
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  4. Yushu Zhang
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Contributions

Xiuli Chai: Conceptualization, Validation, Formal analysis and investigation, Writing-original draft preparation, Writing-review and editing, Data curation. Guoqiang Long: Writing-original draft preparation, Software, Data curation. Zhihua Gan: Conceptualization, Writing-review and editing, Data curation. Yushu Zhang: Conceptualization, Methodology, Software. All authors have read and agreed to the final version of the manuscript.

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Correspondence to Xiuli Chai or Zhihua Gan.

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Chai, X., Long, G., Gan, Z. et al. TPE-MM: Thumbnail preserving encryption scheme based on Markov model for JPEG images. Appl Intell 54, 3429–3447 (2024). https://doi.org/10.1007/s10489-024-05318-z

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