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Christian A. Hammerschmidt
Christian A. Hammerschmidt
APTA Technologies B.V.
Verified email at tudelft.nl - Homepage
Title
Cited by
Cited by
Year
Generating multi-categorical samples with generative adversarial networks
R Camino, C Hammerschmidt, R State
arXiv preprint arXiv:1807.01202, 2018
472018
Improving missing data imputation with deep generative models
RD Camino, CA Hammerschmidt, R State
arXiv preprint arXiv:1902.10666, 2019
43*2019
BotGM: Unsupervised graph mining to detect botnets in traffic flows
S Lagraa, J François, A Lahmadi, M Miner, C Hammerschmidt, R State
Cyber Security in Networking Conference (CSNet), 2017 1st, 1-8, 2017
292017
flexfringe: A Passive Automaton Learning Package
SE Verwer, C Hammerschmidt
Software Maintenance and Evolution (ICSME), 2017 IEEE International …, 2017
232017
Learning behavioral fingerprints from Netflows using Timed Automata
G Pellegrino, Q Lin, C Hammerschmidt, S Verwer
Integrated Network and Service Management (IM), 2017 IFIP/IEEE Symposium on …, 2017
202017
Efficient Learning of Communication Profiles from IP Flow Records
C Hammerschmidt, S Marchal, R State, G Pellegrino, S Verwer
Local Computer Networks (LCN), 2016 IEEE 41st Conference on, 559-562, 2016
162016
Short-term time series forecasting with regression automata
Q Lin, C Hammerschmidt, G Pellegrino, S Verwer
162016
Behavioral clustering of non-stationary IP flow record data
C Hammerschmidt, S Marchal, R State, S Verwer
Network and Service Management (CNSM), 2016 12th International Conference on …, 2016
12*2016
State R.(2019)
R Camino, CA Hammerschmidt
Improving Missing Data Imputation with Deep Generative Models. ArXiv abs …, 1902
12*1902
Beyond labeling: Using clustering to build network behavioral profiles of malware families
A Nadeem, C Hammerschmidt, CH Gañán, S Verwer
Malware Analysis Using Artificial Intelligence and Deep Learning, 381-409, 2021
92021
Interpreting Finite Automata for Sequential Data
CA Hammerschmidt, S Verwer, Q Lin, R State
arXiv preprint arXiv:1611.07100, 2016
72016
Reliable Machine Learning for Networking: Key Issues and Approaches
CA Hammerschmidt, S Garcia, S Verwer, R State
Local Computer Networks (LCN), 2017 IEEE 42nd Conference on, 167-170, 2017
62017
Federated learning for cyber security: SOC collaboration for malicious URL detection
E Khramtsova, C Hammerschmidt, S Lagraa, R State
2020 IEEE 40th International Conference on Distributed Computing Systems …, 2020
52020
The robust malware detection challenge and greedy random accelerated multi-bit search
S Verwer, A Nadeem, C Hammerschmidt, L Bliek, A Al-Dujaili, ...
Proceedings of the 13th ACM Workshop on Artificial Intelligence and Security …, 2020
42020
Radu State. Improving missing data imputation with deep generative models
CAHRD Camino, CA Hammerschmidt
arXiv preprint arXiv:1902.10666, 2019
42019
Learning deterministic finite automata from infinite alphabets
G Pellegrino, C Hammerschmidt, Q Lin, S Verwer
International Conference on Grammatical Inference, 120-131, 2017
42017
Malpaca: Malware packet sequence clustering and analysis
A Nadeem, C Hammerschmidt, CH Ganán, S Verwer
arXiv preprint arXiv:1904.01371, 2019
32019
Working with deep generative models and tabular data imputation
RD Camino, C Hammerschmidt
22020
Oversampling Tabular Data with Deep Generative Models: Is it worth the effort?
RD Camino, CA Hammerschmidt
PMLR, 2020
22020
FlexFringe: Modeling Software Behavior by Learning Probabilistic Automata
S Verwer, C Hammerschmidt
arXiv preprint arXiv:2203.16331, 2022
12022
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