Abstract
Digital forensics is gaining increasing momentum today thanks to rapid developments in data editing technologies. We propose and implement a novel image forensics technique that incorporates hexadecimal image analysis to detect forgery in still images. The simple and effective algorithm we developed yields promising results identifying the tool used for forgery with zero false positives. Moreover, it is comparable to other known image forgery detection algorithms with respect to runtime performance.
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Acknowledgments
The authors would like to thank Danny Choi, Zijia Ding, and Brandon Lam for helping contribute to the initial prototype that inspired us to pursue this work.
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Fossati, G., Agarwal, A., Cankaya, E.C. (2021). Digital Image Forensics Using Hexadecimal Image Analysis. In: Zallio, M., Raymundo Ibañez, C., Hernandez, J.H. (eds) Advances in Human Factors in Robots, Unmanned Systems and Cybersecurity. AHFE 2021. Lecture Notes in Networks and Systems, vol 268. Springer, Cham. https://doi.org/10.1007/978-3-030-79997-7_22
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DOI: https://doi.org/10.1007/978-3-030-79997-7_22
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