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Johan Mazel
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Books and Theses
- 2011
- [b1]Johan Mazel:
Unsupervised network anomaly detection. (Détection non supervisée d'anomalies dans les réseaux de communication). INSA Toulouse, France, 2011
Journal Articles
- 2021
- [j5]Ha Dao
, Johan Mazel, Kensuke Fukuda
:
CNAME Cloaking-Based Tracking on the Web: Characterization, Detection, and Protection. IEEE Trans. Netw. Serv. Manag. 18(3): 3873-3888 (2021) - 2019
- [j4]Johan Mazel, Richard Garnier, Kensuke Fukuda:
A comparison of web privacy protection techniques. Comput. Commun. 144: 162-174 (2019) - 2015
- [j3]Johan Mazel, Pedro Casas, Romain Fontugne, Kensuke Fukuda, Philippe Owezarski:
Hunting attacks in the dark: clustering and correlation analysis for unsupervised anomaly detection. Int. J. Netw. Manag. 25(5): 283-305 (2015) - 2012
- [j2]Pedro Casas, Johan Mazel, Philippe Owezarski:
Unsupervised Network Intrusion Detection Systems: Detecting the Unknown without Knowledge. Comput. Commun. 35(7): 772-783 (2012) - [j1]Pedro Casas, Johan Mazel, Philippe Owezarski:
Knowledge-independent traffic monitoring: Unsupervised detection of network attacks. IEEE Netw. 26(1): 13-21 (2012)
Conference and Workshop Papers
- 2021
- [c19]Corentin Larroche, Johan Mazel, Stéphan Clémençon:
Anomalous Cluster Detection in Large Networks with Diffusion-Percolation Testing. ESANN 2021 - 2020
- [c18]Corentin Larroche, Johan Mazel, Stéphan Clémençon:
Percolation-Based Detection of Anomalous Subgraphs in Complex Networks. IDA 2020: 287-299 - 2018
- [c17]Ha Dao, Johan Mazel, Kensuke Fukuda:
Understanding abusive web resources: characteristics and counter-measures of malicious web resources and cryptocurrency mining. AINTEC 2018: 54-61 - 2017
- [c16]Johan Mazel, Romain Fontugne, Kensuke Fukuda:
Profiling internet scanners: Spatiotemporal structures and measurement ethics. TMA 2017: 1-9 - 2016
- [c15]Johan Mazel, Romain Fontugne, Kensuke Fukuda:
Identifying Coordination of Network Scans Using Probed Address Structure. TMA 2016 - 2015
- [c14]Romain Fontugne, Patrice Abry
, Kensuke Fukuda, Pierre Borgnat
, Johan Mazel, Herwig Wendt
, Darryl Veitch:
Random projection and multiscale wavelet leader based anomaly detection and address identification in internet traffic. ICASSP 2015: 5530-5534 - [c13]Romain Fontugne
, Johan Mazel, Kensuke Fukuda
:
An empirical mixture model for large-scale RTT measurements. INFOCOM 2015: 2470-2478 - 2014
- [c12]Romain Fontugne, Johan Mazel, Kensuke Fukuda
:
Hashdoop: A MapReduce framework for network anomaly detection. INFOCOM Workshops 2014: 494-499 - [c11]Pedro Casas, Johan Mazel, Philippe Owezarski:
Coping with 0-day attacks through Unsupervised Network Intrusion Detection. IWCMC 2014: 24-29 - [c10]Johan Mazel, Romain Fontugne, Kensuke Fukuda:
A taxonomy of anomalies in backbone network traffic. IWCMC 2014: 30-36 - [c9]Johan Mazel, Romain Fontugne, Kensuke Fukuda:
Visual comparison of network anomaly detectors with chord diagrams. SAC 2014: 473-480 - 2012
- [c8]Johan Mazel, Hiroshi Esaki, Romain Fontugne, Kensuke Fukuda:
Improving an SVD-based combination strategy of anomaly detectors for traffic labelling. AINTEC 2012: 69-76 - 2011
- [c7]Johan Mazel, Pedro Casas, Yann Labit, Philippe Owezarski:
Sub-Space clustering, Inter-Clustering Results Association & anomaly correlation for unsupervised network anomaly detection. CNSM 2011: 1-8 - [c6]Pedro Casas, Johan Mazel, Philippe Owezarski:
On the use of Sub-Space Clustering & Evidence Accumulation for traffic analysis & classification. IWCMC 2011: 1016-1021 - [c5]Pedro Casas, Johan Mazel, Philippe Owezarski:
UNADA: Unsupervised Network Anomaly Detection Using Sub-space Outliers Ranking. Networking (1) 2011: 40-51 - [c4]Pedro Casas, Johan Mazel, Philippe Owezarski:
Steps Towards Autonomous Network Security: Unsupervised Detection of Network Attacks. NTMS 2011: 1-5 - [c3]Pedro Casas, Johan Mazel, Philippe Owezarski:
MINETRAC: Mining flows for unsupervised analysis & semi-supervised classification. ITC 2011: 87-94 - [c2]Johan Mazel, Pedro Casas, Philippe Owezarski:
Sub-Space Clustering and Evidence Accumulation for Unsupervised Network Anomaly Detection. TMA 2011: 15-28 - 2010
- [c1]Philippe Owezarski, Johan Mazel, Yann Labit:
0day Anomaly Detection Made Possible Thanks to Machine Learning. WWIC 2010: 327-338
Informal and Other Publications
- 2022
- [i4]Johan Mazel, Matthieu Saudrais, Antoine Hervieu:
ML-based tunnel detection and tunneled application classification. CoRR abs/2201.10371 (2022) - 2021
- [i3]Corentin Larroche, Johan Mazel, Stéphan Clémençon:
Dynamically Modelling Heterogeneous Higher-Order Interactions for Malicious Behavior Detection in Event Logs. CoRR abs/2103.15708 (2021) - 2019
- [i2]Johan Mazel, Rémi Strullu:
Identifying and characterizing ZMap scans: a cryptanalytic approach. CoRR abs/1908.04193 (2019) - 2017
- [i1]Johan Mazel, Richard Garnier, Kensuke Fukuda:
A comparison of web privacy protection techniques. CoRR abs/1712.06850 (2017)
Coauthor Index
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