| A close look on n-grams in intrusion detection: anomaly detection vs. classification C Wressnegger, G Schwenk, D Arp, K Rieck Proceedings of the 2013 ACM workshop on Artificial intelligence and security …, 2013 | 128 | 2013 |
| Botzilla: detecting the" phoning home" of malicious software K Rieck, G Schwenk, T Limmer, T Holz, P Laskov Proceedings of the 2010 ACM symposium on applied computing, 1978-1984, 2010 | 122 | 2010 |
| Adaptive detection of covert communication in http requests G Schwenk, K Rieck 2011 Seventh European Conference on Computer Network Defense, 25-32, 2011 | 26 | 2011 |
| Autonomous learning for detection of javascript attacks: Vision or reality? G Schwenk, A Bikadorov, T Krueger, K Rieck Proceedings of the 5th ACM Workshop on Security and Artificial Intelligence …, 2012 | 19 | 2012 |
| Detecting behavioral and structural anomalies in mediacloud applications G Schwenk, S Bach arXiv preprint arXiv:1409.8035, 2014 | 4 | 2014 |
| Classification of structured validation data using stateless and stateful features G Schwenk, R Pabst, KR Müller Computer Communications 138, 54-66, 2019 | 3 | 2019 |
| Features spaces and a learning system for structural-temporal data, and their application on a use case of real-time communication network validation data G Schwenk, B Jochinke, KR Müller Plos one 15 (2), e0228434, 2020 | | 2020 |
| Features and Machine Learning Systems for Structured and Sequential Data G Schwenk PQDT-Global, 2019 | | 2019 |
