Cover-source mismatch in steganalysis: systematic review

Abstract

Operational steganalysis contends with a major problem referred to as the cover-source mismatch (CSM), which is essentially a difference in distribution caused by different parameters and settings over training and test data. Despite it being of fundamental importance in an 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.