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Cerioli, A, Barabesi, L, Cerasa, A, Menegatti, M and Perrotta, D (2019). Newcomb-Benford law and the detection of frauds in international trade. Proceedings of the National Academy of Sciences 116(1), pp. 106-115.

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Azevedo, CdS, Gonçalves, RF, Gava, VL and Spinola, MdM (2021). A Benford’s Law based methodology for fraud detection in social welfare programs: Bolsa Familia analysis. Physica A 567, p. 125626. DOI:10.1016/j.physa.2020.125626. View Complete Reference Online information Works that this work references Works that reference this work
Barabesi, L, Cerasa, A, Cerioli, A and Perotta, D (2021). A combined test of the Benford Hypothesis With Anti-fraud Applications. Proceedings of 13th Scientific Meeting of the Classification and Data Analysis Group, Florence, September 9-11. STAMPA, pp. 256-259. DOI:10.36253/978-88-5518-340-6. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Barabesi, L, Cerasa, A, Cerioli, A and Perrotta, D (2021). On characterizations and tests of Benford’s law. Journal of the American Statistical Association. DOI:10.1080/01621459.2021.1891927. View Complete Reference Online information Works that this work references Works that reference this work
Barabesi, L, Cerioli, A and Di Marzio, M (2023). Statistical models and the Benford hypothesis: a unified framework. TEST. DOI:10.1007/s11749-023-00881-y. View Complete Reference Online information Works that this work references Works that reference this work
Barabesi, L, Cerioli, A and Perrotta, D (2021). Forum on Benford’s law and statistical methods for the detection of frauds. Statistical Methods & Applications 30, pp. 767–778. DOI:10.1007/s10260-021-00588-0. View Complete Reference Online information Works that this work references Works that reference this work
Barabesi, L and Pratelli, L (2020). On the Generalized Benford law. Statistics & Probability Letters 160, 108702 . DOI:10.1016/j.spl.2020.108702. View Complete Reference Online information Works that this work references Works that reference this work
Cerasa, A (2022). Testing for Benford’s Law in very small samples: Simulation study and a new test proposal. PLoS ONE 17(7), pp. e0271969. DOI:10.1371/journal.pone.0271969. View Complete Reference Online information Works that this work references Works that reference this work
Cerioli, A, Barabesi, L, Cerasa, A and Perrotta, D (2022). Who is afraid of the probability-savvy fraudster?. Conference presentation at MBC2 2022 Models and Learning for Clustering and Classification 6th International Workshop, Catania. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Chen, T and Tsourakakis, CE (2022). AntiBenford Subgraphs: Unsupervised Anomaly Detection in Financial Networks. Preprint arXiv:2205.13426 [cs.; last accessed June 9, 2022. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Crisan, D and Gota, DI (2023). The First-Digit Law application in digital forensics in crystal forgery research. Proceedings of 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), Tenerife, Canary Islands, Spain, pp. 1-7. DOI:10.1109/ICECCME57830.2023.10253354. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Cuenca, AV (2023). La Ley de Benford, Del Primer Dígito Significativo. Trabajo Fin de Grado en Matemáticas, Universidad de Valladolid . SPA View Complete Reference Online information Works that this work references No Bibliography works reference this work
D'Alessandro, A (2020). Benford's law and metabolomics: A tale of numbers and blood. Transfusion and Apheresis Science 59(6), pp. 103019. DOI:10.1016/j.transci.2020.103019. View Complete Reference Online information Works that this work references Works that reference this work
Ducharme, RG, Kaci, S and Vovor-Dassu ,C (2020). Smooths Tests of Goodness-of-fit for the Newcomb-Benford distribution. Preprint: arXiv:2003.00520v1 [math.ST]. Published in Mathématiques appliquées et stochastiques, 3(1). FRE View Complete Reference Online information Works that this work references Works that reference this work
Eckhartt, GM and Ruxton, GD (2023). Investigating and preventing scientific misconduct using Benford’s Law. Research Integrity and Peer Review 8(1). DOI:10.1186/s41073-022-00126-w. View Complete Reference Online information Works that this work references Works that reference this work
Ensminger, J and Leder-Luis, J (2022). Measuring Strategic Data Manipulation: Evidence from a World Bank Project. Preprint, submitted for publication. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Ensminger, J and Leder-Luis, J (2022). Detecting Fraud in Development Aid. Preprint. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Ergin, E and Erturan, IE (2020). Is Benford’s Law Effective in Fraud Detection for Expense Cycle? . Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi 42(2), pp. 316–326. DOI:10.14780.muiibd.854444. View Complete Reference Online information Works that this work references Works that reference this work
Fernandes, P, Ó Ciardhuáin, S and Antunes, M (2024). Uncovering Manipulated Files Using Mathematical Natural Laws. In: Vasconcelos, V., Domingues, I., Paredes, S. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2023. Lecture Notes in Computer Science, vol 14469. Springer, Cham . DOI:10.1007/978-3-031-49018-7_4. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Filho, DF, Silva, L and Medeiros, H (2022). “Won’t get fooled again”: statistical fault detection in COVID-19 Latin American data. Globalization and Health 18, pp.105. DOI:10.1186/s12992-022-00899-1. View Complete Reference Online information Works that this work references Works that reference this work
Gao, J, Zhao, Y and Cui, R (2020). Research on the Applicability of Benford’s Law in Chinese Texts. Proceedings of 2nd International Conference on Artificial Intelligence and Advanced Manufacture (AIAM), Manchester, United Kingdom, pp. 13-17. DOI:10.1109/AIAM50918.2020.00009. View Complete Reference Online information Works that this work references Works that reference this work
Hulme, PE, Ahmed, DA, Haubrock, PJ, Kaiser, BA, Kourantidou, M, Leroy, B and McDermott, SM (2023). Widespread imprecision in estimates of the economic costs of invasive alien species worldwide. Science of the Total Environment, pp. 167997. DOI:10.1016/j.scitotenv.2023.167997. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Kalameyets, M, Levshun, D, Soloviev, S, Chechulin, A and Kotenko, I (2020). Social networks bot detection using Benford’s law. SIN 2020: 13th International Conference on Security of Information and Networks, Article No.: 19. pp. 1–8. DOI:10.1145/3433174.3433589. View Complete Reference Online information Works that this work references Works that reference this work
Kauko, K (2024). How to detect what drives deviations from Benford’s law? An application to bank deposit data. Empir. Econ (2024). View Complete Reference Online information Works that this work references Works that reference this work
Kennedy, AP and Yam, SCP (2020). On the authenticity of COVID-19 case figures. PLoS ONE 15(12): e0243123. DOI:10.1371/journal.pone.0243123. View Complete Reference Online information Works that this work references Works that reference this work
Lacasa, L (2019). Newcomb–Benford law helps customs officers to detect fraud in international trade. Proceedings of the National Academy of Sciences 116(1), pp. 11-13. DOI:10.1073/pnas.1819470116. View Complete Reference Online information Works that this work references Works that reference this work
Martínez JW, Martínez JC, Rincón DA, Salazar, DA, Castrillón JD, Gómez MDP, Suárez OF, Vélez JP, Valencia ÁM, Gómez S, Rincón ÁM, Idrovo ÁJ, Moreno-Montoya J, Prieto-Alvarado FE, Hurtado-Ortiz A and (2020). Benchmarking of public health surveillance of COVID-19 in Colombia: First semester. Biomedica : Revista del Instituto Nacional de Salud 40(Supl. 2), pp. 198-204. SPA View Complete Reference Online information Works that this work references No Bibliography works reference this work
Morag, S and Salmon-Divon, M (2019). Characterizing Human Cell Types and Tissue Origin Using the Benford Law. Cells 8(9), p. 1004. DOI:10.3390/cells8091004. View Complete Reference Online information Works that this work references Works that reference this work
Moreau, VH (2021). Inconsistencies in Countries COVID-19 Data Revealed by Benford’s Law’. Model Assisted Statistics and Applications 16(1), pp. 73-79. DOI:10.3233/MAS-210517. View Complete Reference Online information Works that this work references Works that reference this work
Morillas-Jurado, FG, Caballer-Tarazona, M and Caballer-Tarazona, V (2022). Applying Benford’s Law to Monitor Death Registration Data: A Management Tool for the COVID-19 Pandemic. Mathematics 10(1), 46. DOI:10.3390/math10010046. View Complete Reference Online information Works that this work references Works that reference this work
Mumic, N and Filzmoser, P (2021). A multivariate test for detecting fraud based on Benford’s law, with application to music streaming data. Statistical Methods & Applications 30, 819–840. DOI:10.1007/s10260-021-00582-6. View Complete Reference Online information Works that this work references Works that reference this work
O'Mahony, L, O'Sullivan, DJP and Nikolov, NS (2023). On the Detection of Anomalous or Out-of-Distribution Data in Vision Models Using Statistical Techniques.. In: Proceedings of the 3rd International Conference on Artificial Intelligence and Computer Vision (AICV2023), March 5–7, 2023. AICV 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 164. Springer, Cham.. DOI:10.1007/978-3-031-27762-7_40. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Perrotta, D, Cerasa, A, Barabesi, L and Menegatti, M (2019). Contamination And Manipulation Of Trade Data: The Two Faces Of Customs Fraud . Book of Short Papers, Proceedings of the 12th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society (SIS), pp. 394-397. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Renaldo, N, Hutahuruk, MB and Putri, IY (2022). Forensic Accounting: The Use of Benford's Law to Evaluate Indications of Fraud . Revista Eletrônica do Departamento de Ciências Contábeis & Departamento de Atuária e Métodos Quantitativos (REDECA) 9(e57343), pp. 1-15. DOI:10.23925/2446-9513.2022v9id57343. View Complete Reference No online information available Works that this work references Works that reference this work
Scholes, CA (2023). Applying the significant-digit law to simplify grading of chemical engineering students design projects. Australasian Journal of Engineering Education. DOI:10.1080/22054952.2023.2247292. View Complete Reference Online information Works that this work references Works that reference this work
Scholes, CA (2023). Utilising forensic tools to assist in chemical engineering capstone assessment grading. Education for Chemical Engineers 45, pp. 61-67 . DOI:10.1016/j.ece.2023.08.001. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Silva, LEdO and Figueiredo, D (2024). A novel approach to evaluate data integrity: evidence from COVID-19 in China. Brazilian Journal of Biometrics 42(1), pp. 78-87. DOI:10.28951/bjb.v42i1.659. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Vovor-Dassu, KC (2021). Tests d'adéquation à la loi de Newcomb-Benford comme outils de détection de fraudes. PhD Thesis L’Universite de Montpellier. DOI:10.13140/RG.2.2.12559.25764. FRE View Complete Reference Online information Works that this work references No Bibliography works reference this work
Wang, H, Liu, T, Zhang, Y, Wu, Y, Sun, Y, Dong, J and Huang, W (2023). Last Digit Tendency: Lucky Numbers and Psychological Rounding in Mobile Transactions. Fundamental Research. DOI:10.1016/j.fmre.2023.11.011. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Wang, L and Ma, B-Q (2023). A concise proof of Benford’s law. Fundamental Research . DOI:10.1016/j.fmre.2023.01.002. View Complete Reference Online information Works that this work references Works that reference this work
Zhang, J (2020). Testing Case Number of Coronavirus Disease 2019 in China with Newcomb-Benford Law. Preprint arXiv:2002.05695 [physics.soc-ph]; last accessed February 18, 2020. View Complete Reference Online information Works that this work references Works that reference this work