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Color image steganalysis based on channel gradient correlation

Author

Listed:
  • Yuhan Kang
  • Fenlin Liu
  • Chunfang Yang
  • Lingyun Xiang
  • Xiangyang Luo
  • Ping Wang

Abstract

It is one of the potential threats to the Internet of Things to reveal confidential messages by color image steganography. The existing color image steganalysis algorithm based on channel geometric transformation measures owns higher accuracy than the others, but it fails to utilize the correlation between the gradient amplitudes of different color channels. Therefore, this article points out that the color image steganography weakens the correlation between the gradient amplitudes of different color channels and proposes a color image steganalysis algorithm based on channel gradient correlation. The proposed algorithm extracts the co-occurrence matrix feature from the gradient amplitude residuals among different color channels and then combines it with the existing color image steganalysis features to train the ensemble classifier for color image steganalysis. The experimental results show that, for WOW and S-UNIWARD steganography, compared with the existing algorithms, the proposed algorithm outperforms the existing algorithms.

Suggested Citation

  • Yuhan Kang & Fenlin Liu & Chunfang Yang & Lingyun Xiang & Xiangyang Luo & Ping Wang, 2019. "Color image steganalysis based on channel gradient correlation," International Journal of Distributed Sensor Networks, , vol. 15(5), pages 15501477198, May.
    • Handle: RePEc:sae:intdis:v:15:y:2019:i:5:p:1550147719852031
    DOI: 10.1177/1550147719852031
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    Cited by:

    1. Chunfang Yang & Yuhan Kang & Fenlin Liu & Xiaofeng Song & Jie Wang & Xiangyang Luo, 2020. "Color image steganalysis based on embedding change probabilities in differential channels," International Journal of Distributed Sensor Networks, , vol. 16(5), pages 15501477209, May.

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