| System log clustering approaches for cyber security applications: A survey M Landauer, F Skopik, M Wurzenberger, A Rauber Computers & Security 92, 101739, 2020 | 107 | 2020 |
| Dynamic log file analysis: An unsupervised cluster evolution approach for anomaly detection M Landauer, M Wurzenberger, F Skopik, G Settanni, P Filzmoser computers & security 79, 94-116, 2018 | 85 | 2018 |
| Deep learning for anomaly detection in log data: A survey M Landauer, S Onder, F Skopik, M Wurzenberger Machine Learning with Applications 12, 100470, 2023 | 77 | 2023 |
| Incremental clustering for semi-supervised anomaly detection applied on log data M Wurzenberger, F Skopik, M Landauer, P Greitbauer, R Fiedler, ... Proceedings of the 12th International Conference on Availability …, 2017 | 53 | 2017 |
| A framework for cyber threat intelligence extraction from raw log data M Landauer, F Skopik, M Wurzenberger, W Hotwagner, A Rauber 2019 IEEE International Conference on Big Data (Big Data), 3200-3209, 2019 | 39 | 2019 |
| Have it your way: Generating customized log datasets with a model-driven simulation testbed M Landauer, F Skopik, M Wurzenberger, W Hotwagner, A Rauber IEEE Transactions on Reliability 70 (1), 402-415, 2020 | 37 | 2020 |
| Time series analysis: unsupervised anomaly detection beyond outlier detection M Landauer, M Wurzenberger, F Skopik, G Settanni, P Filzmoser Information Security Practice and Experience: 14th International Conference …, 2018 | 27 | 2018 |
| Dealing with security alert flooding: using machine learning for domain-independent alert aggregation M Landauer, F Skopik, M Wurzenberger, A Rauber ACM Transactions on Privacy and Security 25 (3), 1-36, 2022 | 25 | 2022 |
| Aecid-pg: A tree-based log parser generator to enable log analysis M Wurzenberger, M Landauer, F Skopik, W Kastner 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM), 7-12, 2019 | 20 | 2019 |
| synERGY: Cross-correlation of operational and contextual data to timely detect and mitigate attacks to cyber-physical systems F Skopik, M Landauer, M Wurzenberger, G Vormayr, J Milosevic, J Fabini, ... Journal of Information Security and Applications 54, 102544, 2020 | 18 | 2020 |
| Maintainable log datasets for evaluation of intrusion detection systems M Landauer, F Skopik, M Frank, W Hotwagner, M Wurzenberger, ... IEEE Transactions on Dependable and Secure Computing 20 (4), 3466-3482, 2022 | 17 | 2022 |
| Smart Log Data Analytics F Skopik, M Wurzenberger, M Landauer Springer International Publishing, 2021 | 16 | 2021 |
| Enabling exercises, education and research with a comprehensive cyber range. M Leitner, M Frank, G Langner, M Landauer, F Skopik, P Smith, B Akhras, ... J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl. 12 (4), 37-61, 2021 | 13 | 2021 |
| Aminer: A modular log data analysis pipeline for anomaly-based intrusion detection M Landauer, M Wurzenberger, F Skopik, W Hotwagner, G Höld Digital Threats: Research and Practice 4 (1), 1-16, 2023 | 12 | 2023 |
| Online log data analysis with efficient machine learning: A review F Skopik, M Landauer, M Wurzenberger IEEE Security & Privacy 20 (3), 80-90, 2021 | 10 | 2021 |
| Behavior-based anomaly detection in log data of physical access control systems F Skopik, M Wurzenberger, G Höld, M Landauer, W Kuhn IEEE Transactions on Dependable and Secure Computing 20 (4), 3158-3175, 2022 | 9 | 2022 |
| A framework for automatic labeling of log datasets from model-driven testbeds for HIDS evaluation M Landauer, M Frank, F Skopik, W Hotwagner, M Wurzenberger, ... Proceedings of the 2022 ACM Workshop on Secure and Trustworthy Cyber …, 2022 | 8 | 2022 |
| Blind spots of security monitoring in enterprise infrastructures: a survey F Skopik, M Landauer, M Wurzenberger IEEE Security & Privacy 20 (6), 18-26, 2022 | 8 | 2022 |
| Creating character-based templates for log data to enable security event classification M Wurzenberger, G Höld, M Landauer, F Skopik, W Kastner Proceedings of the 15th ACM Asia Conference on Computer and Communications …, 2020 | 8 | 2020 |
| Analysis of statistical properties of variables in log data for advanced anomaly detection in cyber security M Wurzenberger, G Höld, M Landauer, F Skopik Computers & Security 137, 103631, 2024 | 7 | 2024 |
Florian SkopikAIT Austrian Institute of Technology在 ait.ac.at 的电子邮件经过验证
