Color image steganalysis based on channel gradient correlation

Yuhan Kang, Fenlin Liu, Chunfang Yang, Lingyun Xiang, Xiangyang Luo and Ping Wang

International Journal of Distributed Sensor Networks, 2019, vol. 15, issue 5, 1550147719852031

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.

Keywords: Color image; steganalysis; gradient; steganography; texture (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:15:y:2019:i:5:p:1550147719852031

DOI: 10.1177/1550147719852031

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