In batch steganography, the sender distributes the secret payload among multiple images from a “bag” to decrease the chance of being caught. Recent work on this topic described an experimentally discovered phenomenon, which we call the “bag gain”: for fixed communication rate, pooled detectors experience a decrease in statistical detectability for initially increasing bag sizes, providing an opportunity for the sender to gain in security. The bag gain phenomenon is universal in the sense of manifesting under a wide spectrum of conditions. In this paper, we explain this experimental observation by adopting a statistical model of detector response. Despite the simplicity of the model, it does capture observed trends in detectability as a function of the bag size, the rate, and cover source properties. Additionally, and surprisingly, the model predicts that in certain cover sources the sender should avoid bag sizes that are too small as this can lead to a bag loss.
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Observing Bag Gain in JPEG Batch Steganography
The bag gain relates to a gain in security due to spreading payload among multiple covers when the steganog- rapher maintains a positive communication rate. This gain is maximal for a certain optimal bag size, which depends on the embedding method, payload spreading strategy, communication rate, and the cover source. Originally discovered and analyzed in the spatial domain, in this paper we study this phenomenon for JPEG images across quality factors. Our experiments and theoretical analysis indicate that the bag gain is more pronounced for higher JPEG qualities, more aggressive batch senders, and for senders maintaining a fixed payload per bag in terms of bits per DCT rather than per non-zero AC DCT.
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- Award ID(s):
- 2028119
- PAR ID:
- 10451150
- Date Published:
- Journal Name:
- IEEE Workshop on Information Security and Forensics
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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