Forensic Data Model for Artificial Intelligence based Media Forensics - Illustrated on the Example of DeepFake Detection

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Abstract

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.

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Siegel, D., Seidlitz, S., Kraetzer, C., & Dittmann, J. (2022). Forensic Data Model for Artificial Intelligence based Media Forensics - Illustrated on the Example of DeepFake Detection. In IS and T International Symposium on Electronic Imaging Science and Technology (Vol. 34). Society for Imaging Science and Technology. https://doi.org/10.2352/EI.2022.34.4.MWSF-324

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