Study of cover source mismatch in steganalysis and ways to mitigate its impact

Author:

Kodovský Jan,Sedighi Vahid,Fridrich Jessica

Publisher

SPIE

Reference22 articles.

1. Information Hiding

2. A theory of learning from different domains

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4. Practical methods for minimizing embedding impact in steganography;Fridrich,2007

5. Rich Models for Steganalysis of Digital Images

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1. Image steganography approaches and their detection strategies: a survey;ACM Computing Surveys;2024-09-10

2. Cover-source mismatch in steganalysis: systematic review;EURASIP Journal on Information Security;2024-08-12

3. Are Deepfakes a Game-changer in Digital Images Steganography Leveraging the Cover-Source-Mismatch?;Proceedings of the 19th International Conference on Availability, Reliability and Security;2024-07-30

4. Statistical Correlation as a Forensic Feature to Mitigate the Cover-Source Mismatch;Proceedings of the 2024 ACM Workshop on Information Hiding and Multimedia Security;2024-06-24

5. RCDD: Contrastive domain discrepancy with reliable steganalysis labeling for cover source mismatch;Expert Systems with Applications;2024-03

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