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Kobiela, J and Dzierwa, P (2024)

Application of Benford’s Law to the Identification of Non-authentic Digital Images

Proceedings of the 22nd International Conference on Advances in Mobile Computing and Multimedia Intelligence, MoMM 2024, held in Bratislava, Slovak Republic, pp. 115-129 .

ISSN/ISBN: Not available at this time. DOI: 10.1007/978-3-031-78049-3_12



Abstract: This study evaluated Benford’slaw for detecting non-authentic digital images by analyzing the first digits of pixel values after a discrete cosine transform (DCT). We analyzed 137 pairs of authentic and modified JPEGs using ROC curves, k-means clustering, chi-squared tests, and PCA. The results showed AUC values near 0.5, indicating low classification performance. The k-means algorithm had 49% precision with low completeness, and PCA revealed a significant overlap between the authentic and manipulated images. These findings suggest the limited effectiveness of Benford’s law alone, highlighting the need to integrate advanced image-processing methods and explore additional pixel-distribution features for the effective detection of non-authentic images.


Bibtex:
@incollection{, author = {Jarek Kobiela and Piotr M. Dzierwa}, title = {Application of Benford’s Law to the Identification of Non-authentic Digital Images}, booktitle = {Proceedings of the 22nd International Conference on Advances in Mobile Computing and Multimedia Intelligence} publisher = {Springer Nature}, year = {2024}, pages = {115--129}, month = {dec} doi = {10.1007/978-3-031-78049-3_12}, url = {https://link.springer.com/chapter/10.1007/978-3-031-78049-3_12}, }


Reference Type: Conference Paper

Subject Area(s): Image Processing