Visual Information Processing and Protection Group
The Visual Information Processing and Protection (VIPP) group is an informal research group belonging to the Laboratory of Telematics and Telecommunications (LTT) of the Department of Information Engineering and Mathematics of the University of Siena.
The VIPP Group was founded in 2005 and it currently consists of 10 members:
1 Professor, 2 post-doc researchers, 2 PhD students, 3 visiting PhD students and 2 research fellows.
The research interests of the VIPP group span the whole area of Multimedia Security and Adversarial Signal and Information Processing, with a particular focus on the protection and authentication of visual information.
Other research areas of the VIPP group include Adversarial signal and information processing, Machine Learning applications for Digital Forensics, Distributed detection in adversarial setting, Data hiding and watermarking and Signal Processing in the Encrypted Domain.
Currently, the most active research area is Multimedia Forensics, with special emphasis on Adversarial Image Forensics, that is the development of media forensic techniques designed in such a way to withstand the attacks of one or more adversaries aiming at system failure. This research activity is partially funded by DARPA (U.S.) through the Medifor project.
The VIPP group is especially devoted to keep a high quality research standard, and for this reason it adopts and pushes the Reproducible Signal Processing (RSP) paradigm, whereby the reproducibility of the experimental part of the researches carried out by the group is ensured by providing a precise description of the experiments and, whenever possible, by sharing the software produced by the group with other researchers.
The group welcomes students and researchers wishing to spend a self-funded, research period within the group. Expression of interest should be submitted, together with a CV, to Prof. Mauro Barni.
The VIPP group is looking for new PhD candidates and post-doc researchers.
In both cases the research activity will regard the development of multimedia forensic tools explicitly devoted to detect tampered and artificial images and videos in adversarial setting.
With regard to the post-doc positions, it is required prior experience in multimedia forensics, machine learning, AI, and an excellent publication record.