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Li, XH, Zhao, YQ, Liao, M, Shih, FY and Shi, YQ (2012). Detection of tampered region for JPEG images by using mode-based first digit features. EURASIP Journal on Advances in Signal Processing, 2012:190.

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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
Iorliam, A, Emmanual, O and Shehu, YI (2021). An Investigation of "Benford's" Law Divergence and Machine Learning Techniques for "Intra-Class" Separability of Fingerprint Images. Preprint arXiv:2201.01699 [cs.CV]; last accessed January 12, 2022. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Iorliam, A, Ho, AT, Poh, N, Zhao, X and Xia, Z (2017). Benford's law for classification of biometric images. In: User-Centric Privacy and Security in Biometrics, Claus Vielhauer (Ed.). ISSN/ISBN:9781785612077. DOI:10.1049/PBSE004E_ch11. View Complete Reference Online information Works that this work references Works that reference this work
Iorliam, A, Ho, ATS, Poh, N and Shi, YQ (2014). Do Biometric Images Follow Benford's Law?. Proceedings of the 22nd European Signal Processing Conf.(Eusipco). DOI:10.1109/IWBF.2014.6914261. View Complete Reference Online information Works that this work references Works that reference this work
Iorliam, A, Ho, ATS, Waller, A and Zhao, X (2017). Using Benford's Law Divergence and Neural Networks for Classification and Source Identification of Biometric Images. In: Shi Y., Kim H., Perez-Gonzalez F., Liu F. (eds) Digital Forensics and Watermarking. IWDW 2016. Lecture Notes in Computer Science, vol 10082. Springer, Cham, pp. 88-105. DOI:10.1007/978-3-319-53465-7_7. View Complete Reference Online information Works that this work references Works that reference this work
Iorliam, A and Shangbum, FC (2017). On the Use of Benford’s Law to Detect JPEG Biometric Data Tampering. Journal of Information Security 8, pp. 240-256. DOI:10.4236/jis.2017.83016. View Complete Reference Online information Works that this work references Works that reference this work
Iorliam, A, Tirunagari, S, Ho, ATS, Li, S, Waller, A and Poh, N (2017). "Flow Size Difference" Can Make a Difference: Detecting Malicious TCP Network Flows Based on Benford's Law. arXiv:1609.04214v2 [cs.CR], last accessed February 6, 2017. View Complete Reference Online information Works that this work references Works that reference this work
Joksimović, D, Knežević, G, Pavlović, V, Ljubić, M and Surovy, V (2017). Some Aspects of the Application of Benford’s Law in the Analysis of the Data Set Anomalies. In: Knowledge Discovery in Cyberspace: Statistical Analysis and Predictive Modeling. New York: Nova Science Publishers, pp. 85–120. ISSN/ISBN:978-1-53610-566-7. View Complete Reference Online information Works that this work references Works that reference this work
Mire, A, Dhok, SB, Mistry, NJ and Porey, PD (2016). Tampering Localization in Digital Image Using First Two Digit Probability Features. In: Satapathy, S., Mandal, J., Udgata, S., Bhateja, V. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 435. Springer, New Delhi, pp. 133-151. DOI:10.1007/978-81-322-2757-1_15. View Complete Reference Online information Works that this work references Works that reference this work
Parnak, A, Damavandi, YB and Kazemitabar, SJ (2022). A Novel Image Splicing Detection Algorithm based on Generalized and Traditional Benford’s Law. International Journal of Engineering, Transactions A: Basics 35(4), pp. 626-634. View Complete Reference Online information Works that this work references Works that reference this work
Satapathy, G, Bhattacharya, G, Puhan, NB and Ho, ATS (2020). Generalized Benford’s Law for Fake Fingerprint Detection. Proceedings of 2020 IEEE Applied Signal Processing Conference (ASPCON), Kolkata, pp. 242-246. DOI:10.1109/ASPCON49795.2020.9276660. View Complete Reference Online information Works that this work references Works that reference this work
Sethi, K, Kumar, R, Prajapati, N and Bera, P (2020). A Lightweight Intrusion Detection System using Benford's Law and Network Flow Size Difference. Proceedings of 2020 International Conference on COMmunication Systems NETworkS (COMSNETS). DOI:10.1109/COMSNETS48256.2020.9027422. View Complete Reference Online information Works that this work references Works that reference this work
Sun, L, Ho, ATS, Xia, Z, Chen, J, Huang, X and Zhang, Y (2017). Detection and Classification of Malicious Patterns In Network Traffic Using Benford’s Law. 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Kuala Lumpur, pp. 864-872. DOI:10.1109/APSIPA.2017.8282154. View Complete Reference Online information Works that this work references Works that reference this work