| System log clustering approaches for cyber security applications: A survey M Landauer, F Skopik, M Wurzenberger, A Rauber Computers & Security 92, 101739, 2020 | 126 | 2020 |
| 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 | 120 | 2023 |
| 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 | 89 | 2018 |
| 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 | 58 | 2017 |
| 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 | 49 | 2020 |
| Protecting cyber physical production systems using anomaly detection to enable self-adaptation G Settanni, F Skopik, A Karaj, M Wurzenberger, R Fiedler 2018 IEEE Industrial Cyber-Physical Systems (ICPS), 173-180, 2018 | 46 | 2018 |
| 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 | 43 | 2019 |
| Acquiring Cyber Threat Intelligence through Security Information Correlation G Settanni, Y Shovgenya, F Skopik, R Graf, M Wurzenberger, R Fiedler Cybernetics (CYBCONF), 2017 3rd IEEE International Conference on, 1-7, 2017 | 38 | 2017 |
| 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 | 31 | 2018 |
| 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 | 29 | 2022 |
| AECID: A Self-learning Anomaly Detection Approach Based on Light-weight Log Parser Models M Wurzenberger, F Skopik, G Settanni, R Fiedler 4th International Conference on Information Systems Security and Privacy …, 2018 | 28 | 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 | 26 | 2022 |
| Complex log file synthesis for rapid sandbox-benchmarking of security-and computer network analysis tools M Wurzenberger, F Skopik, G Settanni, W Scherrer Information Systems 60, 13-33, 2016 | 24 | 2016 |
| 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 | 21 | 2019 |
| Correlating cyber incident information to establish situational awareness in Critical Infrastructures G Settanni, Y Shovgenya, F Skopik, R Graf, M Wurzenberger, R Fiedler Privacy, Security and Trust (PST), 2016 14th Annual Conference on, 78-81, 2016 | 21 | 2016 |
| Towards a resilience metric framework for cyber-physical systems I Friedberg, K McLaughlin, P Smith, M Wurzenberger 4th International Symposium for ICS & SCADA Cyber Security Research 2016, 19-22, 2016 | 21 | 2016 |
| A Critical Review of Common Log Data Sets Used for Evaluation of Sequence-based Anomaly Detection Techniques M Landauer, F Skopik, M Wurzenberger arXiv preprint arXiv:2309.02854, 2023 | 20 | 2023 |
| Smart Log Data Analytics F Skopik, M Wurzenberger, M Landauer Springer International Publishing, 2021 | 18 | 2021 |
| 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 |
| 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 | 17 | 2024 |
Florian SkopikAIT Austrian Institute of TechnologyE-mailová adresa ověřena na: ait.ac.at