| Title | An Effective Steganalysis for Robust Steganography with Repetitive JPEG Compression |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Feng, Jinliu, Wang, Yaofei, Chen, Kejiang, Zhang, Weiming, Yu, Nenghai |
| Conference Name | ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
| Date Published | may |
| Keywords | composability, feature combination, Image coding, Manuals, Metrics, Perturbation methods, privacy, pubcrawl, Repetitive Compression, Robust Steganography, Signal processing, social networking (online), steganalysis, steganography, steganography detection, Transform coding |
| Abstract | With the development of social networks, traditional covert communication requires more consideration of lossy processes of Social Network Platforms (SNPs), which is called robust steganography. Since JPEG compression is a universal processing of SNPs, a method using repeated JPEG compression to fit transport channel matching is recently proposed and shows strong compression-resist performance. However, the repeated JPEG compression will inevitably introduce other artifacts into the stego image. Using only traditional steganalysis methods does not work well towards such robust steganography under low payload. In this paper, we propose a simple and effective method to detect the mentioned steganography by chasing both steganographic perturbations as well as continuous compression artifacts. We introduce compression-forensic features as a complement to steganalysis features, and then use the ensemble classifier for detection. Experiments demonstrate that this method owns a similar and better performance with respect to both traditional and neural-network-based steganalysis. |
| Notes | ISSN: 2379-190X |
| DOI | 10.1109/ICASSP43922.2022.9747061 |
| Citation Key | feng_effective_2022 |
An Effective Steganalysis for Robust Steganography with Repetitive JPEG Compression