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A Multi-level Sorting Prediction Enhancement-Based Two-Dimensional Reversible Data Hiding Algorithm for JPEG Images

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Science of Cyber Security (SciSec 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14299))

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Abstract

To improve the performance of reversible data hiding on JPEG images, a multi-level sorting prediction enhancement-based two-dimensional reversible data hiding algorithm for JPEG images is proposed in this paper. Firstly, the smoothness of each DCT block is evaluated by counting the number of non-zero AC coefficients in each DCT block. Then, the gradient of the object block is calculated with the DC coefficients of its surrounding blocks, and the lowest gradient direction blocks are employed to achieve the prediction of object block AC coefficients. The AC coefficient in the object block is accurately predicted by AC coefficients in the same position of its adjacent blocks. These chosen adjacent blocks are located in the lowest gradient direction. Then, the obtained DCT coefficient prediction errors are paired by a similar prediction-error pairing strategy to construct a two-dimensional prediction-error histogram. Finally, the secret data are imperceptibly embedded into the AC coefficients by using the two-dimensional histogram shifting algorithm. The performance multi-level sorting prediction enhancement-based two-dimensional reversible data hiding algorithm was validated on different classical images, and six representative images were elaborately chosen to demonstrate the superiority of the proposed scheme. Extensive experimental results show that, compared to other state-of-the-art reversible data hiding algorithms, the proposed algorithm can achieve higher marked image visual quality while maintaining low JPEG image file size increments.

This work was partially supported by National Natural Science Foundation of China (62272255); National key research and development program of China (2021YFC3340602); Shandong Provincial Natural Science Foundation Innovation and Development Joint Fund (ZR202208310038); Ability Improvement Project of Science and Technology SMES in Shandong Province (2022TSGC2485); Project of Jinan Research Leader Studio (2020GXRC056); Project of Jinan Introducing Innovation Team (202228016); Project of Jinan City-School Integration Development (JNSX2021030); Youth Innovation Team of Colleges and Universities in Shandong Province (2022KJ124) The “Chunhui Plan” Cooperative Scientific Research Project of Ministry of Education (HZKY20220482) Shandong Provincial Natural Science Foundation (ZR2020MF054).

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Authors and Affiliations

  1. Shandong Provincial Key Laboratory of Computer Networks, Jinan, 250000, China

    Bin Ma, Songkun Wang, Chunpeng Wang & Jian Li

  2. Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250000, China

    Bin Ma, Songkun Wang, Chunpeng Wang & Jian Li

  3. Shandong University of Finance and Economics, Jinan, 250000, China

    Jian Xu

  4. Beijing Jiaotong University, Beijing, 100044, China

    Xiaolong Li

Authors
  1. Bin Ma
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  2. Songkun Wang
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  3. Jian Xu
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  4. Chunpeng Wang
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  5. Jian Li
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  6. Xiaolong Li
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Corresponding author

Correspondence to Jian Xu .

Editor information

Editors and Affiliations

  1. Columbia University, New York, NY, USA

    Moti Yung

  2. RMIT University, Melbourne, VIC, Australia

    Chao Chen

  3. Technical University of Denmark, Kongens Lyngby, Denmark

    Weizhi Meng

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Ma, B., Wang, S., Xu, J., Wang, C., Li, J., Li, X. (2023). A Multi-level Sorting Prediction Enhancement-Based Two-Dimensional Reversible Data Hiding Algorithm for JPEG Images. In: Yung, M., Chen, C., Meng, W. (eds) Science of Cyber Security . SciSec 2023. Lecture Notes in Computer Science, vol 14299. Springer, Cham. https://doi.org/10.1007/978-3-031-45933-7_28

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  • DOI: https://doi.org/10.1007/978-3-031-45933-7_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-45932-0

  • Online ISBN: 978-3-031-45933-7

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