CUING

The increasing number of Internet users, availability of storage and network resources, and proliferation of as-a-Service frameworks, leads to a new-wave of offensive campaigns targeting the virtual world. With the diffusion of improved defensive methods, attackers now utilize more and more sophisticated techniques to perform their malicious activities. In recent years, information hiding has emerged as one of the most sophisticated and effective mechanisms for launching attacks. Threat actors now regularly use information hiding to elude countermeasures and prevent reversing the attack chain. More recently, hiding techniques have been deployed to create covert channels, i.e., parasitic communications paths nested in network traffic and digital objects, mainly to cloak command & control communications. Unfortunately, detection and mitigation of threats taking advantage of information hiding are hard tasks that pose many new challenges for digital forensics analysts, academics, law enforcement agencies, and security professionals.

The aim of the International Workshop on Cyber Use of Information Hiding (CUIng) is to bring together researchers, practitioners, law enforcement representatives, and security professionals in the area of analysis of information hiding techniques when used in cyberspace. Techniques, mechanisms, and ideas that fall in the scope of the workshop are not limited to classic digital steganography applications or the creation and mitigation of covert communications. Therefore, CUIng also welcomes works that pertain to camouflaging/masking/hiding various types of data, e.g., identities, behaviors of processes, and communication flows. To present a more complete picture of the novel research on hiding methods and their utilization by the attackers, submissions dealing with impersonation or mimicking are encouraged as well, especially to address information hiding in a complete manner, for instance, to discuss ideas for fighting misuse of privacy-enhancing technologies.

This year the CUING workshop is co-organized together with DISSIMILAR (Detection of fake newS on SocIal MedIa pLAtfoRms) project.

Moreover, the extended versions of all accepted papers will be considered for publication in a special issue of the Journal of Cyber Security and Mobility (indexed in Scopus).

Keynote: 

Statistical Models of digital images for Adversarial Methods in steganography and AI-based generation

While a vast majority of digital image forensics approaches are based on machine learning and, recently, exploits the extremely high accuracy of deep learning, these approaches generally provide a low-level of understanding and interpretability.
In the speech, we will present statistical models that allow assessing detectability of information hidden in digital images. We will review how such models can be used to design original adversarial methods that minimizes the statistical detectability.
Last, but not least, we will study the possible application of a similar adversarial method for AI-based generation of digital images.

About the speaker:

Rémi Cogranne received the Ph.D. degree in systems safety and optimization from the University of Technology of Troyes (UTT), France, in 2011. He was regularly invited as a Visiting Scholar with Binghamton University, from 2014 to 2020. He has been an Associate Professor with UTT, since 2013. His research interests include hypothesis testing applied to image forensics, steganalysis, steganography, and computer networks. He has published more than 80 articles, among which two received the best paper awards, and three International patents. He is an Elected Member of IEEE Technical Committee on IFS a member of the Editorial Board of several international journals and conferences. He has been the general chair of IEEE WIFS 2022, the General Chair of ACM IH&MMSec 2019, the TPC Chair of IEEE WIFS 2021, and the Main Organizer of ALASKA Steganalysis Challenge (https://alaska.utt.fr).