Cross Reference Up

Iorliam, A, Ho, ATS, Poh, N, Tirunagari, S and Bours, P (2015). Data forensic techniques using 
Benford’s law and Zipf’s law for keystroke dynamics. In: Proceedings of 3rd International Workshop on 
Biometrics and Forensics (IWBF 2015). IEEE, pp. 1–6.

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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
Iorliam, A (2019). Combination of Natural Laws (Benford’s Law and Zipf’s Law) for Fake News Detection. In: Cybersecurity in Nigeria. SpringerBriefs in Cybersecurity. Springer, Cham. DOI:10.1007/978-3-030-15210-9_3. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Iorliam, A (2019). Natural Laws (Benford’s Law and Zipf’s Law) for Network Traffic Analysis. In: Cybersecurity in Nigeria. SpringerBriefs in Cybersecurity. Springer, Cham, pp. 3-22. ISSN/ISBN:978-3-030-15210-9. DOI:10.1007/978-3-030-15210-9_2. View Complete Reference Online information Works that this work references Works that reference this work
Jianu, Io, Isaic-Maniu, A, Brandas, C, Cristescu, MP, Bente, C and Herteliu, C (2023). Testing benford and universal laws on gambling and betting data in Romania. Annals of Operations Research. DOI:10.1007/s10479-023-05739-y. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Maurus, S and Plant, C (2017). Let's See Your Digits: Anomalous-State Detection using Benford's Law. Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2017, pp. 977–986. DOI:10.1145/3097983.3098101. View Complete Reference Online information Works that this work references Works that reference this work
Tirunagari, S, Abasolo, D, Iorliam, A, Ho, ATS and Poh, N (2017). Using Benford’s Law to Detect Anomalies in Electroencephalogram: An Application to Detecting Alzheimer’s Disease. In: Proceedings of 2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), Manchester, 2017, pp. 1-6. DOI:10.1109/CIBCB.2017.8058547. View Complete Reference Online information Works that this work references Works that reference this work