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Christian A. Hammerschmidt
Christian A. Hammerschmidt
APTA Technologies B.V.
Bestätigte E-Mail-Adresse bei tudelft.nl - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Generating multi-categorical samples with generative adversarial networks
R Camino, C Hammerschmidt, R State
arXiv preprint arXiv:1807.01202, 2018
442018
Improving missing data imputation with deep generative models
RD Camino, CA Hammerschmidt, R State
arXiv preprint arXiv:1902.10666, 2019
42*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
272017
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
192017
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
152016
Short-term time series forecasting with regression automata
Q Lin, C Hammerschmidt, G Pellegrino, S Verwer
152016
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
72021
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
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
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
32020
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
FlexFringe: Modeling Software Behavior by Learning Probabilistic Automata
S Verwer, C Hammerschmidt
arXiv preprint arXiv:2203.16331, 2022
12022
Oversampling Tabular Data with Deep Generative Models: Is it worth the effort?
RD Camino, CA Hammerschmidt
PMLR, 2020
12020
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