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Prandl, S (2017). PEIMA: Harnessing Power Laws to Detect Malicious Activities from Denial of Service to Intrusion Detection Traffic Analysis and Beyond. Black Hat USA.

This work cites the following items of the Benford Online Bibliography:

Arshadi, L and Jahangir, AH (2014). Benford's law behavior of Internet traffic. Journal of Network and Computer Applications, Volume 40, April 2014, pp. 194–205. ISSN/ISBN:1084-8045. DOI:10.1016/j.jnca.2013.09.007. View Complete Reference Online information Works that this work references Works that reference this work
Durtschi, C, Hillison, W and Pacini, C (2004). The effective use of Benford’s law to assist in detecting fraud in accounting data. Journal of Forensic Accounting 1524-5586/Vol. V, pp. 17-34. View Complete Reference Online information Works that this work references Works that reference this work
Gottwalt, F, Waller, A and Liu, W (2016). Natural Laws as a Baseline for Network Anomaly Detection. In: Proceedings of 2016 IEEE Trustcom/BigDataSE/ISPA, pp. 370-377. DOI:10.1109/TrustCom.2016.0086. View Complete Reference Online information Works that this work references Works that reference this work
Iorliam, A (2016). Application of power laws to biometrics, forensics and network traffic analysis. PhD Thesis, University of Surrey. View Complete Reference Online information Works that this work references Works that reference this work
Lesperance, M, Reed, WJ, Stephens, MA, Tsao, C and Wilton, B (2016). Assessing Conformance with Benford’s Law: Goodness-Of-Fit Tests and Simultaneous Confidence Intervals. PLoS One 11(3): e0151235; published online 2016 Mar 28. DOI:10.1371/journal.pone.0151235. View Complete Reference Online information Works that this work references Works that reference this work
Pietronero, L, Tosatti, E, Tosatti, V and Vespignani, A (2001). Explaining the uneven distribution of numbers in nature: the laws of Benford and Zipf. Physica A - Statistical Mechanics and its Applications 293(1-2), 297-304. ISSN/ISBN:0378-4371. DOI:10.1016/S0378-4371(00)00633-6. View Complete Reference Online information Works that this work references Works that reference this work
Prandl, S, Lazarescu, M, Pham, DS, Soh, ST and Kak, S (2017). An Investigation of Power Law Probability Distributions for Network Anomaly Detection. 2017 IEEE Security and Privacy Workshops (SPW), pp. 217-222, . DOI:10.1109/SPW.2017.20. View Complete Reference Online information Works that this work references Works that reference this work