Cross Reference Down

Swain, M, Nishitha, CL, Maganti, M, Sethi, K and Tripathi, N (2025). Leveraging Benford’s Law for Effective Intrusion Detection in MQTT-IoT Networks. In: Proceedings of 2025 17th International Conference on COMmunication Systems & NETworkS (COMSNETS), pp. 348-355.

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

Benford, F (1938). The law of anomalous numbers. Proceedings of the American Philosophical Society, Vol. 78, No. 4 (Mar. 31, 1938), pp. 551-572. View Complete Reference Online information No Bibliography works referenced by this work. Works that reference this work
Fernandes, P, Ciardhuáin, SÓ and Antunes, M (2024). Unveiling Malicious Network Flows Using Benford’s Law. Mathematics 12(15), p. 2299. DOI:10.3390/math12152299. 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
Jasak, Z and Banjanovic-Mehmedovic, L (2008). Detecting Anomalies by Benford's Law. In Proceedings of IEEE International Symposium on Signal Processing and Information Technology, 2008. ISSPIT 2008, pp. 453-458 . ISSN/ISBN:978-1-4244-3554-8. DOI:10.1109/ISSPIT.2008.4775660. View Complete Reference Online information Works that this work references Works that reference this work
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. DOI:10.1186/1687-6180-2012-190. 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