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
172018
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
162017
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
142017
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
142016
Short-term time series forecasting with regression automata
Q Lin, C Hammerschmidt, G Pellegrino, S Verwer
112016
R. State. Improving missing data imputation with deep generative models
R Camino, C Hammerschmidt
arXiv preprint arXiv:1902.10666, 2019
92019
flexfringe: A Passive Automaton Learning Package
SE Verwer, C Hammerschmidt
Software Maintenance and Evolution (ICSME), 2017 IEEE International …, 2017
92017
Interpreting Finite Automata for Sequential Data
CA Hammerschmidt, S Verwer, Q Lin, R State
arXiv preprint arXiv:1611.07100, 2016
72016
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
72016
Improving missing data imputation with deep generative models
RD Camino, CA Hammerschmidt, R State
arXiv preprint arXiv:1902.10666, 2019
52019
Learning deterministic finite automata from infinite alphabets
G Pellegrino, C Hammerschmidt, Q Lin, S Verwer
International Conference on Grammatical Inference, 120-131, 2017
42017
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
32017
Malpaca: Malware packet sequence clustering and analysis
A Nadeem, C Hammerschmidt, CH Ganán, S Verwer
arXiv preprint arXiv:1904.01371, 2019
22019
Human in the Loop: Interactive Passive Automata Learning via Evidence-Driven State-Merging Algorithms
CA Hammerschmidt, R State, S Verwer
arXiv preprint arXiv:1707.09430, 2017
12017
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
2021
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
2020
Working with Deep Generative Models and Tabular Data Imputation
RD Camino, C Hammerschmidt
2020
Minority Class Oversampling for Tabular Data with Deep Generative Models
R Camino, C Hammerschmidt, R State
arXiv preprint arXiv:2005.03773, 2020
2020
Federated Learning For Cyber Security: SOC Collaboration For Malicious URL Detection
E Khramtsova, C Hammerschmidt, S Lagraa
IEEE International Conference on Distributed Computing Systems (ICDCS), 2020
2020
Auto Semi-supervised Outlier Detection for Malicious Authentication Events
G Kaiafas, C Hammerschmidt, S Lagraa
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2019
2019
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