In the last years many image forensic (IF) algorithms have been proposed to reveal traces of processing or tampering. On the other hand, Anti-Forensic (AF) tools have also been developed to help the forger in removing editing footprints. Inspired by the fact that it is much harder to commit a perfect crime when the forensic analyst uses a multi-clue investigation strategy, we analyse the possibility o ered by the adoption of a data fusion framework in a Counter-Anti-Forensic (CAF) scenario. We do so by adopting a theoretical framework, based on Dempster-Shafer Theory of Evidence, to synergically merge information provided by IF tools and CAF tools, whose goal is to reveal traces introduced by anti-forensic algorithms. The proposed system accounts for the non-trivial relationships between IF and CAF techniques; for example, in some cases the outputs from the former are expected to contradict the output from the latter. We evaluate the proposed method within a representative forensic task, that is splicing detection in JPEG images, with the forger trying to conceal traces using two di erent counter-forensic methods. Results show that decision fusion strongly limits the e ectiveness of AF methods. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Countering anti-forensics by means of data fusion / Marco Fontani; Alessandro Bonchi; Alessandro Piva; Mauro Barni. - STAMPA. - 9028:(2014), pp. 90280Z-90280Z-15. (Intervento presentato al convegno IS&T/SPIE Electronic Imaging tenutosi a S. Francisco (USA) nel 3 - 5 February 2014) [10.1117/12.2039569].
Countering anti-forensics by means of data fusion
PIVA, ALESSANDRO;
2014
Abstract
In the last years many image forensic (IF) algorithms have been proposed to reveal traces of processing or tampering. On the other hand, Anti-Forensic (AF) tools have also been developed to help the forger in removing editing footprints. Inspired by the fact that it is much harder to commit a perfect crime when the forensic analyst uses a multi-clue investigation strategy, we analyse the possibility o ered by the adoption of a data fusion framework in a Counter-Anti-Forensic (CAF) scenario. We do so by adopting a theoretical framework, based on Dempster-Shafer Theory of Evidence, to synergically merge information provided by IF tools and CAF tools, whose goal is to reveal traces introduced by anti-forensic algorithms. The proposed system accounts for the non-trivial relationships between IF and CAF techniques; for example, in some cases the outputs from the former are expected to contradict the output from the latter. We evaluate the proposed method within a representative forensic task, that is splicing detection in JPEG images, with the forger trying to conceal traces using two di erent counter-forensic methods. Results show that decision fusion strongly limits the e ectiveness of AF methods. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.