@inproceedings{51949066f3f34a76a62af292ea4cde99,
title = "UNCOVER: Development of an efficient steganalysis framework for uncovering hidden data in digital media",
abstract = "This paper presents the general goals of Horizon 2020 project UNCOVER, whose overall purpose is to close the gap between academic work and operational needs in the fields of data-hiding. While digital data-hiding is a relatively new area of research, our motivation in this project has been rooted in the growing gap between the academic community and the operational needs of a {"}real-life{"}scenario of object inspection in order to UNCOVER the presence of data secretly hidden. As well as an oversight into the structure of UNCOVER, our paper presents an empirical study on the impact of specifically training a detection method for a given data-hiding scheme, the so-called Stego-Source Mismatch, as an example of unexplored issues that raises important and mostly ignored consequences within the operational context the UNCOVER project targets.",
keywords = "Contest, Cover-Source Mismatch, Data-hiding, Forensics, H2020, Image processing, Security, Steganalysis, Steganography",
author = "Vaila Leask and R{\'e}mi Cogranne and Dirk Borghys and Helena Bruyninckx",
note = "Publisher Copyright: {\textcopyright} 2022 ACM.; 17th International Conference on Availability, Reliability and Security, ARES 2022 ; Conference date: 23-08-2022 Through 26-08-2022",
year = "2022",
month = aug,
day = "23",
doi = "10.1145/3538969.3544468",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
booktitle = "Proceedings of the 17th International Conference on Availability, Reliability and Security, ARES 2022",
}