Name
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 offered 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 different counter-forensic methods. Results show that decision fusion strongly limits the effectiveness of AF methods. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1117/12.2039569 | Proceedings of SPIE |
Keywords | Field | DocType |
Counter Forensics,Image Forensics,Data Fusion,Multi-clue decision | Data mining,Decision fusion,Commit,Sensor fusion,JPEG,Image forensics,Merge (version control),Information fusion,Theory of evidence,Physics | Conference |
Volume | ISSN | Citations |
9028 | 0277-786X | 4 |
PageRank | References | Authors |
0.39 | 11 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marco Fontani | 1 | 198 | 14.07 |
| alessandro bonchi | 2 | 4 | 0.39 |
| Alessandro Piva | 3 | 2231 | 157.21 |
| M. Barni | 4 | 3091 | 246.21 |