Algorithm Mismatch in Spatial Steganalysis

Reinders, Stephanie; Lin, Li; Guan, Yong Liang; Wu, Min; Newman, Jennifer

doi:10.2352/issn.2470-1173.2019.5.mwsf-535

Cited by 2 publications

(2 citation statements)

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“…Pushing forward in this direction, the steps of the IPP are usually studied in isolation, but their order might impact the CSM. Interactions between the steps exist, e.g., between resampling and sharpening [Abe+22] or between SSM and the cover source [Rei+19].…”

Section: Discussionmentioning

confidence: 99%

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Cover-Source Mismatch in Steganalysis: Systematic Review

Mallet,

Benes,

Cogranne

2024

Preprint

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Operational steganalysis contends with a major problem referred to as the cover-source mismatch (CSM), which is essentially a change of distribution caused by different parameters and settings over training and test data. Despite it being of fundamental importance in operational context, the CSM problem is often overlooked in the literature. With the goal to increase the visibility of this problem and attract the interest of the community, the present paper proposes a systematic review of the literature. It summarizes gathered knowledge and major open questions over the last 20 years of active research on CSM: terminology, methods of measurement, known causes, and mitigation strategies. Over 100 papers exploring, mitigating, assessing or discussing steganalysis under train-test mismatch were collected by sampling scholar databases, and tracing references, cited and generated. For image steganalysis, the literature provided enough evidence to quantify the impact of causes, and the effectiveness of mitigation strategies.

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Section: Discussionmentioning

confidence: 99%

“…The literature uses either "stego-source mismatch" (SSM) [DBF16; Lea+22], and "stego-algorithm mismatch" (SAM) [Rei+19]. We suggest a new name, stego-scheme mismatch (SSM), because it is more general and hence encompasses the few possible causes of the mismatch of this kind.…”

Section: Mismatch In Steganographymentioning

confidence: 99%