Overview of the ImageCLEFsecurity 2019: File Forgery Detection Tasks

Resumen

The File Forgery Detection tasks is in its first edition, in 2019. This year, it is composed by three subtasks: a) Forged file discovery, b) Stego image discovery and c) Secret message discovery. The data set contained 6,400 images and pdf files, divided into 3 sets. There were 61 participants and the majority of them participated in all the subtasks. This highlights the major concern the scientific community shows for security issues and the importance of each subtask. Submissions varied from a) 8, b) 31 and c) 14 submissions for each subtask, respectively. Although the datasets were small, most of the participants used deep learning techniques, especially in subtasks 2 & 3. The results obtained in subtask 3-which was the most difficult one-showed that there is room for improvement, as more advanced techniques are needed to achieve better results. Deep learning techniques adopted by many researchers is a preamble in that direction, and proved that they may provide a promising steganalysis tool to a digital forensics examiner.