Simulating Suboptimal Steganographic Embedding
Author(s) -
Christy Kin-Cleaves,
Andrew D. Ker
Publication year - 2020
Publication title -
oxford university research archive (ora) (university of oxford)
Language(s) - English
Resource type - Conference proceedings
ISBN - 978-1-4503-7050-9
DOI - 10.1145/3369412.3395071
Subject(s) - steganography , embedding , computer science , coding (social sciences) , distortion (music) , benchmark (surveying) , information hiding , algorithm , artificial intelligence , pattern recognition (psychology) , mathematics , statistics , telecommunications , amplifier , geodesy , bandwidth (computing) , geography
Researchers who wish to benchmark the detectability of steganographic distortion functions typically simulate stego objects. However, the difference (coding loss) between simulated stego objects, and real stego objects is significant, and dependent on multiple factors. In this paper, we first identify some factors affecting the coding loss, then propose a method to estimate and correct for coding loss by sampling a few covers and messages. This allows us to simulate suboptimally-coded stego objects which are more accurate representations of real stego objects. We test our results against real embeddings, and naive PLS simulation, showing our simulated stego objects are closer to real embeddings in terms of both distortion and detectability. This is the case even when only a single image and message as used to estimate the loss.
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