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2025 | OriginalPaper | Chapter

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

Authors : Jaroslaw Kobiela, Piotr Dzierwa

Published in: Advances in Mobile Computing and Multimedia Intelligence

Publisher: Springer Nature Switzerland

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Abstract

This study evaluated Benford’s law 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.

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Title: Application of Benford’s Law to the Identification of Non-authentic Digital Images
Authors: Jaroslaw Kobiela
Piotr Dzierwa
Publisher: Springer Nature Switzerland
Book: Advances in Mobile Computing and Multimedia Intelligence
Print ISBN: 978-3-031-78048-6

Electronic ISBN: 978-3-031-78049-3

Copyright Year: 2025
DOI: https://doi.org/10.1007/978-3-031-78049-3_12

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