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Graham, SDJ, Hasseldine, J and Paton, D (2009). Statistical fraud detection in a commercial lobster fishery. New Zealand Journal of Marine and Freshwater Research Volume 43, Issue 1, pp. 457-463.

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Cerri, J (2018). A fish rots from the head down: how to use the leading digits of ecological data to detect their falsification. Preprint, bioRxiv p. 368951. DOI:10.1101/368951. View Complete Reference Online information Works that this work references Works that reference this work
Domínguez- Bustos, AR, Cabrera-Castro, R, Ramos, ML, Abaunza, P and Báez, JC (2024). Using Benford's Law to Detect Possible Biases in Reported Catches of Tropical Tuna From the Indian Ocean. Fisheries Management and Ecology, p. e12749. DOI:10.1111/fme.12749. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Frunza, M-C (2016). Solving Modern Crime in Financial Markets: Analytics and Case Studies. Academic Press, New York, (Chapter 2K) pp. 233-245. DOI:10.1016/B978-0-12-804494-0.00017-6. View Complete Reference Online information Works that this work references Works that reference this work
Miller, SJ (ed.) (2015). Benford's Law: Theory and Applications. Princeton University Press: Princeton and Oxford. ISSN/ISBN:978-0-691-14761-1. View Complete Reference Online information Works that this work references Works that reference this work
Noleto-Filho, EM, Carvalho, AR, Thomè-Souza, MJF and Angelini, R (2022). Reporting the accuracy of small–scale fishing data by simply applying Benford’s law. Frontiers in Marine Science 9, pp. 947503. DOI:10.3389/fmars.2022.947503. View Complete Reference Online information Works that this work references Works that reference this work
Tsagbey, S, de Carvalho, M and Page, GL (2017). All Data are Wrong, but Some are Useful? Advocating the Need for Data Auditing . The American Statistician, 71, pp. 231--235. DOI:10.1080/00031305.2017.1311282. View Complete Reference Online information Works that this work references Works that reference this work