| Generating Multi-Categorical Samples with Generative Adversarial Networks R Camino, C Hammerschmidt, R State arXiv preprint arXiv:1807.01202, 2018 | 17 | 2018 |
| 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 | 15 | 2017 |
| 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 | 13 | 2017 |
| 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 | 13 | 2016 |
| Short-term time series forecasting with regression automata Q Lin, C Hammerschmidt, G Pellegrino, S Verwer | 12 | 2016 |
| flexfringe: A Passive Automaton Learning Package SE Verwer, C Hammerschmidt Software Maintenance and Evolution (ICSME), 2017 IEEE International …, 2017 | 10 | 2017 |
| 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 | 10 | 2016 |
| State, R.: Improving missing data imputation with deep generative models RD Camino, CA Hammerschmidt arXiv preprint arXiv:1902.10666, 2019 | 8 | 2019 |
| Interpreting Finite Automata for Sequential Data CA Hammerschmidt, S Verwer, Q Lin, R State arXiv preprint arXiv:1611.07100, 2016 | 7 | 2016 |
| Improving Missing Data Imputation with Deep Generative Models RD Camino, CA Hammerschmidt, R State arXiv preprint arXiv:1902.10666, 2019 | 4 | 2019 |
| Learning deterministic finite automata from infinite alphabets G Pellegrino, C Hammerschmidt, Q Lin, S Verwer International Conference on Grammatical Inference, 120-131, 2017 | 4 | 2017 |
| 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 | 3 | 2017 |
| MalPaCA: Malware Packet Sequence Clustering and Analysis A Nadeem, C Hammerschmidt, CH Gañán, S Verwer arXiv preprint arXiv:1904.01371, 2019 | 1 | 2019 |
| 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 | 1 | 2017 |
| 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 |
Sicco VerwerDelft University of TechnologyVerified email at tudelft.nl
