The recent development of AI systems and their frequent use for classification problems poses a challenge from a forensic perspective. In many application fields like DeepFake detection, black box approaches such as neural networks are commonly used. As a result, the underlying classification models usually lack explainability and interpretability. In order to increase traceability of AI decisions and move a crucial step further towards precise & reproducible analysis descriptions and certifiable investigation procedures, in this paper a domain adapted forensic data model is introduced for media forensic investigations focusing on media forensic object manipulation detection, such as DeepFake detection.
Dennis Siegel, Christian Krätzer, Stefan Seidlitz, Jana Dittmann, "Forensic data model for artificial intelligence based media forensics - Illustrated on the example of DeepFake detection" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Media Watermarking, Security, and Forensics, 2022, pp 324-1 - 324-6, https://doi.org/10.2352/EI.2022.34.4.MWSF-324