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2025 | OriginalPaper | Buchkapitel

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

verfasst von : Jaroslaw Kobiela, Piotr Dzierwa

Erschienen in: Advances in Mobile Computing and Multimedia Intelligence

Verlag: 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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Guera, D., Delp, E.J.: Deepfake video detection using recurrent neural networks. In: 2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Auckland, New Zealand, pp. 1–6. IEEE (2018). https://doi.org/10.1109/AVSS.2018.8639163

Nightingale, S.J., Wade, K.A., Watson, D.G.: Can people identify original and manipulated photos of real-world scenes? Cogn. Res. 2(1), 30 (2017). https://doi.org/10.1186/s41235-017-0067-2CrossRef

Tolosana, R., Vera-Rodriguez, R., Fierrez, J., Morales, A., Ortega-Garcia, J.: Deepfakes and beyond: a survey of face manipulation and fake detection. Inf. Fusion 64, 131–148 (2020). https://doi.org/10.1016/j.inffus.2020.06.014CrossRef

Karras, T., Aila, T., Laine, S., Lehtinen, J.: Progressive growing of GANs for improved quality, stability, and variation. arXiv http://arxiv.org/abs/1710.10196 (2018). Accessed 09 Feb 2024

Vaccari, C., Chadwick, A.: Deepfakes and disinformation: exploring the impact of synthetic political video on deception, uncertainty, and trust in news. Soc. Media + Soc. 6(1), 205630512090340 (2020). https://doi.org/10.1177/2056305120903408

Verdoliva, L.: Media forensics and DeepFakes: an overview. IEEE J. Sel. Top. Signal Process. 14(5), 910–932 (2020). https://doi.org/10.1109/JSTSP.2020.3002101CrossRef

Farid, H.: Image forgery detection. IEEE Signal Process. Mag. 26(2), 16–25 (2009). https://doi.org/10.1109/MSP.2008.931079CrossRef

Abbott, J.: The Digital Darkroom: The Definitive Guide to Photo Editing. Ilex Press, Lewes (2021)

De Kok, R., Rotundo, G.: Benford networks. Stats 5(4), 934–947 (2022). https://doi.org/10.3390/stats5040054CrossRef

10.

Anderson, K.M., Dayaratna, K., Gonshorowski, D., Miller, S.J.: A new benford test for clustered data with applications to American elections. Stats 5(3), 841–855 (2022). https://doi.org/10.3390/stats5030049CrossRef

11.

Singh, N., Bansal, R.: Analysis of Benford’s law in digital image forensics. In: 2015 International Conference on Signal Processing and Communication, ICSC 2015, pp. 413–418 (2015). https://doi.org/10.1109/ICSPCom.2015.7150688

12.

Póth, M., Trpovski, Ž.: Analysis of JPEG digital image compression process. J. Appl. Tech. Educ. Sci. 9(4) (2019). ISSN: 2560-5429. https://doi.org/10.24368/JATES.V9I4.119

13.

Parnak, A., Baleghi Damavandi, Y., Kazemitabar, S.J.: A novel image splicing detection algorithm based on generalized and traditional Benford’s law. IJE 35(04), 626–634 (2022). https://doi.org/10.5829/IJE.2022.35.04A.02CrossRef

14.

Varga, D.: Analysis of Benford’s law for no-reference quality assessment of natural, screen-content, and synthetic images. Electronics 10(19), 2378 (2021). https://doi.org/10.3390/electronics10192378CrossRef

15.

Zago, J.G., Antonelo, E.A., Baldissera, F.L., Saad, R.T.: Benford’s law: what does it say on adversarial images? J. Vis. Commun. Image Represent. 93, 103818 (2022)CrossRef

16.

Bonettini, N., Bestagini, P., Milani, S., Tubaro, S.: On the use of Benford’s law to detect GAN-generated images. In: 2020 25th International Conference on Pattern Recognition (ICPR), Milan, Italy, pp. 5495–5502. IEEE (2021). https://doi.org/10.1109/ICPR48806.2021.9412944

17.

Kazemitabar, J.: Double-crossing Benford’s law. arXiv http://arxiv.org/abs/2105.09812 (2021). Accessed 06 Feb 2024

18.

Satapathy, G., Bhattacharya, G., Puhan, N.B., Ho, A.T.S.: Generalized Benford’s law for fake fingerprint detection. In: 2020 IEEE Applied Signal Processing Conference (ASPCON), Kolkata, India, pp. 242–246. IEEE (2020). https://doi.org/10.1109/ASPCON49795.2020.9276660

19.

Fu,D., Shi, Y.Q., Su, W.: A generalized Benford’s law for JPEG coefficients and its applications in image forensics. Presented at the Electronic Imaging 2007, San Jose, CA, United States, p. 65051L (2007). https://doi.org/10.1117/12.704723

20.

Perez-Gonzalez, F., Heileman, G.L., Abdallah, C.T.: Benford’s lawin image processing. In: 2007 IEEE International Conference on Image Processing, San Antonio, TX, USA, pp. I-405–I-408. IEEE (2007). https://doi.org/10.1109/ICIP.2007.4378977

21.

Frick, R.A., Liu, H., Steinebach, M.: Detecting double compression and splicing using Benfords first digit law. In: Proceedings of the 15th International Conference on Availability, Reliability and Security, Virtual Event Ireland, pp. 1–9. ACM (2020). https://doi.org/10.1145/3407023.3409200

22.

Bodke, M., Mishra, D., Vasani, K., Janjua, J.: Analysis of Benford’s law for image processing, vol. 9, no. 6, p. 7 (2021)

23.

Iorliam, A., Orgem, E., Shehu, Y.I.: An investigation of Benford’s law divergence and machine learning techniques for intra-class separability of fingerprint images. Gazi Univ. J. Sci. Part A: Eng. Innov. 9(3), 211–224 (2022). https://doi.org/10.54287/gujsa.1077430

24.

Iorliam, A., Ho, A.T.S., Waller, A., Zhao, X.: Using Benford’s law divergence and neural networks for classification and source identification of biometric images. In: Shi, Y.Q., Kim, H.J., Perez-Gonzalez, F., Liu, F. (eds.) IWDW 2016. LNCS, vol. 10082, pp. 88–105. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-53465-7_7CrossRef

25.

Goh, C.: Applying visual analytics to fraud detection using Benford’s law. J. Corp. Account. Finance 31(4), 202–208 (2020). https://doi.org/10.1002/jcaf.22440CrossRef

26.

Giudice, O., Guarnera, L., Battiato, S.: Fighting deepfakes by detecting GAN DCT anomalies. J. Imaging 7(8), 128 (2021). https://doi.org/10.3390/jimaging7080128CrossRef

27.

Werner, P., Lopez-Martinez, D., Walter, S., Al-Hamadi, A., Gruss, S., Picard, R.W.: Automatic recognition methods supporting pain assessment: a survey. IEEE Trans. Affect. Comput. 13(1), 530–552 (2022). https://doi.org/10.1109/TAFFC.2019.2946774CrossRef

28.

Von Borries, G.F., Quadros, A.V.C.: ROC app: an application to understand ROC curves. Braz. J. Biom. 40(2) (2022). https://doi.org/10.28951/bjb.v40i2.566

29.

Parodi, S., Verda, D., Bagnasco, F., Muselli, M.: The clinical meaning of the area under a receiver operating characteristic curve for the evaluation of the performance of disease markers. Epidemiol. Health 44, e2022088 (2022). https://doi.org/10.4178/epih.e2022088CrossRef

30.

Jain, A.K.: Data clustering: 50 years beyond K-means. Pattern Recogn. Lett. 31(8), 651–666 (2010). https://doi.org/10.1016/j.patrec.2009.09.011CrossRef

31.

Celebi, M.E., Kingravi, H.A., Vela, P.A.: A comparative study of efficient initialization methods for the k-means clustering algorithm. Expert Syst. Appl. 40(1), 200–210 (2013). https://doi.org/10.1016/j.eswa.2012.07.021CrossRef

32.

Sharpe, D.: Your chi-square test is statistically significant: now what? 20(8) (2015)

33.

Kurita, T.: Principal Component Analysis (PCA). In: Kurita, T. (ed.) Computer Vision, pp. 1–4. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-03243-2_649-1CrossRef

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

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

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

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