| A survey of network-based intrusion detection data sets M Ring, S Wunderlich, D Scheuring, D Landes, A Hotho Computers & Security 86, 147-167, 2019 | 614 | 2019 |
| Flow-based benchmark data sets for intrusion detection M Ring, S Wunderlich, D Grüdl, D Landes, A Hotho Proceedings of the 16th European Conference on Cyber Warfare and Security …, 2017 | 236 | 2017 |
| Flow-based network traffic generation using generative adversarial networks M Ring, D Schlör, D Landes, A Hotho Computers & Security 82, 156-172, 2019 | 162 | 2019 |
| Creation of Flow-Based Data Sets for Intrusion Detection M Ring, S Wunderlich, D Grüdl, D Landes, A Hotho Journal of Information Warfare 16 (4), 40-53, 2017 | 86 | 2017 |
| IP2Vec: Learning Similarities Between IP Addresses M Ring, A Dallmann, D Landes, A Hotho 2017 IEEE International Conference on Data Mining Workshops (ICDMW), 657-666, 2017 | 76 | 2017 |
| Detection of slow port scans in flow-based network traffic M Ring, D Landes, A Hotho PloS one 13 (9), e0204507, 2018 | 53 | 2018 |
| Evaluation of post-hoc XAI approaches through synthetic tabular data J Tritscher, M Ring, D Schlr, L Hettinger, A Hotho Foundations of Intelligent Systems: 25th International Symposium, ISMIS 2020 …, 2020 | 23 | 2020 |
| A toolset for intrusion and insider threat detection M Ring, S Wunderlich, D Grüdl, D Landes, A Hotho Data analytics and decision support for cybersecurity: trends, methodologies …, 2017 | 20 | 2017 |
| Comparison of system call representations for intrusion detection S Wunderlich, M Ring, D Landes, A Hotho International Joint Conference: 12th International Conference on …, 2020 | 17 | 2020 |
| Malware detection on windows audit logs using LSTMs M Ring, D Schlör, S Wunderlich, D Landes, A Hotho Computers & Security 109, 102389, 2021 | 16 | 2021 |
| Technical Report CIDDS-001 data set M Ring, S Wunderlich, D Gruedl, D Landes, A Hotho J. Inf. Warfare 13, 2017 | 14 | 2017 |
| inalu: Improved neural arithmetic logic unit D Schlör, M Ring, A Hotho Frontiers in Artificial Intelligence 3, 71, 2020 | 13 | 2020 |
| ConDist: A Context-Driven Categorical Distance Measure M Ring, F Otto, M Becker, T Niebler, D Landes, A Hotho Machine Learning and Knowledge Discovery in Databases, 251-266, 2015 | 11 | 2015 |
| Financial fraud detection with improved neural arithmetic logic units D Schlör, M Ring, A Krause, A Hotho Mining Data for Financial Applications: 5th ECML PKDD Workshop, MIDAS 2020 …, 2021 | 6 | 2021 |
| A presentation framework for programming in programing lectures M Ebert, M Ring 2016 IEEE Global Engineering Education Conference (EDUCON), 369-374, 2016 | 6 | 2016 |
| Impact of generative adversarial networks on netflow-based traffic classification M Wolf, M Ring, D Landes 13th International Conference on Computational Intelligence in Security for …, 2021 | 4 | 2021 |
| The impact of different system call representations on intrusion detection S Wunderlich, M Ring, D Landes, A Hotho Logic Journal of the IGPL 30 (2), 239-251, 2022 | 3 | 2022 |
| Creation of specific flow-based training data sets for usage behaviour classification F Otto, M Ring, D Landes, A Hotho European Conference on Cyber Warfare and Security, 437, 2016 | 3 | 2016 |
| Combination of statistical and semantic data sources for the improvement of software engineering courses (Vision Paper) M Koch, M Ring, F Otto, D Landes Educational Data Mining 2014, 2014 | 3 | 2014 |
| Automatic Threshold Calculation for the Categorical Distance Measure ConDist. M Ring, D Landes, A Hotho LWA, 52-63, 2015 | 1 | 2015 |
Andreas HothoUniversity of WürzburgZweryfikowany adres z informatik.uni-wuerzburg.de
