This is a list of my publications to date:

Journal articles

Johan Mazel, Pedro Casas, Romain Fontugne, Kensuke Fukuda, Philippe Owezarski: Hunting attacks in the dark: clustering and correlation analysis for unsupervised anomaly detection. Int. Journal of Network Management 25(5): 283-305 (2015). Wiley

Pedro Casas, Johan Mazel, and Philippe Owezarski. Unsupervised network intrusion detection systems: Detecting the unknown without knowledge. Comput. Commun., 35(7):772–783, April 2012. ACM

Pedro Casas, Johan Mazel, and Philippe Owezarski. Knowledge-independent traffic monitoring: Unsupervised detection of network attacks. IEEE Network, 26(1):13 –21, January-February 2012. Special issue on Network traffic monitoring and analysis. IEEEXplore

Conferences

Johan Mazel, Romain Fontugne, and Kensuke Fukuda. Identifying Coordination of Network Scans Using Probed Address Structure. In Proceedings of the 9th Traffic Monitoring and Analysis Workshop (TMA 2017). PDF

Romain Fontugne, Johan Mazel, and Kensuke Fukuda. Characterizing Roles and Spatio-Temporal Relations of C&C Servers in Large-Scale Networks. In Proceedings of the 2016 ACM International on Workshop on Traffic Measurements for Cybersecurity (WTMC 2016). ACM

Johan Mazel, Romain Fontugne, and Kensuke Fukuda. Identifying Coordination of Network Scans Using Probed Address Structure. In Proceedings of the 8th Traffic Monitoring and Analysis Workshop (TMA 2016). PDF

Romain Fontugne, Patrice Abry, Kensuke Fukuda, Pierre Borgnat, Johan Mazel, Herwig Wendt, and Darryl Veitch. Random projection and multiscale wavelet leader based anomaly detection and address identification in internet traffic. In Proceedings of 40th International Conference Acoustics, Speech and Signal Processing (ICASSP 2015), 2015.

Romain Fontugne, Johan Mazel, and Kensuke Fukuda. An empirical mixture model for large scale RTT measurements. In Proceedings of 34th Annual IEEE International Conference on Computer Communications (INFOCOM 2015). Acceptance rate: 19.3%. IEEEXplore

Johan Mazel, Romain Fontugne, and Kensuke Fukuda. A taxonomy of anomalies in backbone network traffic. In Proceedings of 5th International Workshop on TRaffic Analysis and Characterization (TRAC 2014), pages 30–36. IEEEXplore

Romain Fontugne, Johan Mazel, and Kensuke Fukuda. Hashdoop: A mapreduce framework for network anomaly detection. In Proceedings of the Second International Workshop on Security and Privacy in Big Data (BigSecurity 2014), pages 494–499. IEEEXplore

Johan Mazel, Romain Fontugne, and Kensuke Fukuda. Visual comparison of network anomaly detectors with chord diagrams. In Proceedings of the 29th Symposium On Applied Computing (SAC 2014), pages 473–480. Acceptance rate: 33%. ACM

Johan Mazel, Romain Fontugne, Hiroshi Esaki, and Kensuke Fukuda. Improving an svd-based combination strategy of anomaly detectors for traffic labelling. In Proceedings of the 8th Asian Internet Engineering Conference (AINTEC 2012), pages 69–76. ACM

Johan Mazel, Pedro Casas, Yann Labit, and Philippe Owezarski. Sub-space clustering, interclustering results association & anomaly correlation for unsupervised network anomaly detection. In Proceedings of the 7th International Conference on Network and Service Management (CNSM 2011), pages 1–8. Best Student Paper Award Acceptance rate: 14.6%. IEEEXplore

Pedro Casas, Johan Mazel, and Philippe Owezarski. Minetrac: Mining flows for unsupervised analysis & semi-supervised classification. In Proceedings of the 23rd International Teletraffic Congress (ITC 2011), pages 87–94. Acceptance rate: 33%. IEEEXplore

Pedro Casas, Johan Mazel, and Philippe Owezarski. On the use of sub-space clustering evidence accumulation for traffic analysis & classification. In Proceedings of 2nd International Workshop on TRaffic Analysis and Characterization (TRAC 2011), pages 1016 –1021. IEEEXplore

Pedro Casas, Johan Mazel, and Philippe Owezarski. UNADA: Unsupervised network anomaly detection using sub-space outliers ranking. In Proceedings of the 4th IFIP Networking Conference (IFIP Networking 2011), pages 40 – 51. Acceptance rate: 21.8%. ACM

Johan Mazel, Pedro Casas, and Philippe Owezarski. Sub-space clustering & evidence accumulation for unsupervised network anomaly detection. In Proceedings of the 3rd Traffic Monitoring and Analysis Workshop (TMA 2011), pages 15 – 28. Acceptance rate: 26.3%. IEEEXplore

Pedro Casas, Johan Mazel, and Philippe Owezarski. Steps towards autonomous network security: Unsupervised detection of network attacks. In Proceedings of the 4th IFIP International Conference on New Technologies, Mobility and Security (NTMS 2011), pages 1 – 5. Acceptance rate: 31%. IEEEXplore

Philippe Owezarski, Johan Mazel, and Yann Labit. 0day anomaly detection made possible thanks to machine learning. In Proceedings of the 8th Wired/Wireless Internet Communications (WWIC 2010), pages 327–338. Invited paper. ACM

Yann Labit and Johan Mazel. Hidden: Hausdorff distance based intrusion detection approach dedicated to networks. In Proceedings of the 3rd International Conference on Internet Monitoring and Protection (ICIMP 2008), pages 11–16. IEEEXplore