Roland Meier
Roland Meier
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Cited by
Cited by
NetHide: Secure and Practical Network Topology Obfuscation.
R Meier, P Tsankov, V Lenders, L Vanbever, MT Vechev
USENIX Security Symposium, 693-709, 2018
pforest: In-network inference with random forests
C Busse-Grawitz, R Meier, A Dietmüller, T Bühler, L Vanbever
arXiv preprint arXiv:1909.05680, 2019
FeedRank: A tamper-resistant method for the ranking of cyber threat intelligence feeds
R Meier, C Scherrer, D Gugelmann, V Lenders, L Vanbever
2018 10th International Conference on Cyber Conflict (CyCon), 321-344, 2018
itap: In-network traffic analysis prevention using software-defined networks
R Meier, D Gugelmann, L Vanbever
Proceedings of the Symposium on SDN Research, 102-114, 2017
Machine learninģ-based detection of C&C channels with a focus on the locked shields cyber defense exercise
N Känzig, R Meier, L Gambazzi, V Lenders, L Vanbever
2019 11th International Conference on Cyber Conflict (CyCon) 900, 1-19, 2019
(self) driving under the influence: Intoxicating adversarial network inputs
R Meier, T Holterbach, S Keck, M Stähli, V Lenders, A Singla, L Vanbever
Proceedings of the 18th ACM Workshop on Hot Topics in Networks, 34-42, 2019
Detection of malicious remote shell sessions
P Dumont, R Meier, D Gugelmann, V Lenders
2019 11th International Conference on Cyber Conflict (CyCon) 900, 1-20, 2019
ditto: WAN Traffic Obfuscation at Line Rate
R Meier, V Lenders, L Vanbever
NDSS Symposium, 2022
Towards an AI-powered Player in Cyber Defence Exercises
R Meier, A Lavrenovs, K Heinäaro, L Gambazzi, V Lenders
2021 13th International Conference on Cyber Conflict (CyCon), 309-326, 2021
General-Purpose Wireless Distance Sensor
R Meier
Master Thesis. Zurich: ETH Zurich, 2014
Mass surveillance of VoIP calls in the data plane
EC Kirci, M Apostolaki, R Meier, A Singla, L Vanbever
Proceedings of the Symposium on SDN Research, 33-49, 2022
Improving Network Security through Obfuscation
R Meier
ETH Zurich, 2022
In-network Anomaly Detection with Programmable Switches
L Vanbever, R Meier
Evaluating and Defeating Network Flow Classifiers Through Adversarial Machine Learning
R Meier, L Gambazzi, L Vanbever
Machine Learning-based Detection of C&C Channels with a Focus on the Locked Shields Cyber Defense Exercise
S Battle, T Minárik, S Alatalu, S Biondi, M Signoretti, I Tolga, G Visky
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