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Inicio  /  Applied Sciences  /  Vol: 10 Par: 22 (2020)  /  Artículo
ARTÍCULO
TITULO

A False Negative Study of the Steganalysis Tool Stegdetect

Benjamin Aziz    
Jeyong Jung    
Julak Lee and Yong-Tae Chun    

Resumen

In this study, we evaluated one of the modern automated steganalysis tools, Stegdetect, to study its false negative rates when analysing a bulk of images. In so doing, we used JPHide method to embed a randomly generated messages into 2000 JPEG images. The aim of this study is to help digital forensics analysts during their investigations by means of providing an idea of the false negative rates of Stegdetect. This study found that (1) the false negative rates depended largely on the tool?s sensitivity values, (2) the tool had a high false negative rate between the sensitivity values from 0.1 to 3.4 and (3) the best sensitivity value for detection of JPHide method was 6.2. It is therefore recommended that when analysing a huge bulk of images forensic analysts need to take into consideration sensitivity values to reduce the false negative rates of Stegdetect.

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