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Volume: 34 | Article ID: MWSF-324
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Forensic data model for artificial intelligence based media forensics - Illustrated on the example of DeepFake detection
  DOI :  10.2352/EI.2022.34.4.MWSF-324  Published OnlineJanuary 2022
Abstract
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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Dennis Siegel, Christian Krätzer, Stefan Seidlitz, Jana Dittmann, "Forensic data model for artificial intelligence based media forensics - Illustrated on the example of DeepFake detectionin 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

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