Computer Science

Computer Science ›› 2024, Vol. 51 ›› Issue (5): 321-330.doi: 10.11896/jsjkx.231000036

• Information Security • Previous Articles     Next Articles

Adaptive Image Steganography Against JPEG Compression

ZHANG Jinghan, CHEN Wen   

  1. School of Cyber Science and Engineering,Sichuan University,Chengdu 610065,China
  • Received:2023-10-07 Revised:2024-03-01 Online:2024-05-15 Published:2024-05-08
  • About author:ZHANG Jinghan,born in 1998,postgraduate.Her main research interests include image steganography and data mining.
    CHEN Wen,born in 1983,Ph.D,asso-ciate professor,Ph.D supervisor.His main research interests include network security and data mining.
  • Supported by:
    National Key Research and Development Program of China(020YFB1805405,2019QY0800) and NationalNatural Science Foundation of China(62372313,62002248,U19A2068).

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Abstract: Existing network communication systems often employ JPEG compression to reduce communication overhead when transmitting images.However,traditional image steganography techniques lack the ability to withstand JPEG compression.After performing lossy compression on secret images,the secret data is easily destroyed and cannot be extracted correctly.Therefore,designing secure and robust image steganography technology has important practical application value.This paper proposes an adaptive image robust steganography algorithm that is resistant to JPEG compression.Firstly,this paper analyzes the information loss caused by JPEG compression on the carrier image and identify stable texture features that can serve as robust embedding domains for secret information.Based on this,this paper present an adaptive secret information quantization embedding method that adjusts based on image block texture features,embedding the secret information into the texture mean features of image blocks with strong resistance to compression.Finally,the error feedback mechanism is used to adjust the generated confidential image until the secret information extraction error rate reaches the expected value,and a robust stego image resistant to JPEG compression is generated.Comparison experiments on BossBase1.01 demonstrate that the proposed method exhibits robust compression,resistance to detection, and maintains high image quality even after JPEG compression.In comparison to traditional least significant bit(LSB) steganography,Catalan transform-based image steganography(Catalan based Steganography),fixed neural network steganography(FNNS),and robust steganography using autoencoder latent space(RoSteALS),the proposed algorithm effectively reduces the average error rates of information extraction by 49.79%,49.73%,37.38%,and 38.85% respectively,while maintaining superior visual quality compared to Catalan based Steganography,FNNS,and RoSteALS.Additionally,our algorithm demonstrates robustness against StegExpose steganalysis.

Key words: Image steganography, Robust steganography, JPEG Compression

CLC Number: 

  • TP309.2
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