Abstract
The society is becoming increasingly dependent on digital data sources. However, our trust on the sources and its contents is only ensured if we can also rely on robust methods that prevent fraudulent forgery. As digital forensic experts are continually dealing with the detection of forged data, new fraudulent approaches are emerging, making it difficult to use automated systems. This security breach is also a good challenge that motivates researchers to explore computational solutions to efficiently address the problem. This paper describes a weighted rule-based system for file forgery detection. The system was developed and validated in the several tasks of ImageCLEFsecurity 2019 track challenge, where promising results were obtained.
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Acknowledgements
This work was supported by the projects NETDIAMOND (POCI-01-0145-FEDER-016385) and SOCA (CENTRO-01-0145-FEDER-000010), co-funded by Centro 2020 program, Portugal 2020, European Union. JRA is funded by the National Science Foundation (FCT), under the grant SFRH/BD/147837/2019.
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Almeida, J.R., Fajarda, O., Oliveira, J.L. (2020). File Forgery Detection Using a Weighted Rule-Based System. In: Arampatzis, A., et al. Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2020. Lecture Notes in Computer Science(), vol 12260. Springer, Cham. https://doi.org/10.1007/978-3-030-58219-7_8
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