Research output per year
Research output per year
Research output
- 19 results
Search results
-
2024
A Critical Review of Common Log Data Sets Used for Evaluation of Sequence-Based Anomaly Detection Techniques
Landauer, M., Skopik, F. & Wurzenberger, M., 12 Jul 2024, In: Proceedings of the ACM on Software Engineering. 1, FSE, p. 1354 - 1375 61.Research output: Contribution to journal › Article › peer-review
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Analysis of statistical properties of variables in log data for advanced anomaly detection in cyber security
Wurzenberger, M., Höld, G., Landauer, M. & Skopik, F., Feb 2024, In: Computers & Security. 137, 14 p., 103631.Research output: Contribution to journal › Article › peer-review
Open Access -
Anomaly detection in log-event sequences: A federated deep learning approach and open challenges
Himler, P., Landauer, M., Skopik, F. & Wurzenberger, M., Jun 2024, In: Machine Learning with Applications. 16, 14 p.Research output: Contribution to journal › Article › peer-review
Open Access -
2023
AMiner: A Modular Log Data Analysis Pipeline for Anomaly-based Intrusion Detection
Landauer, M., Wurzenberger, M., Skopik, F., Hotwagner, W. & Höld, G., 31 Mar 2023, In: Digital Threats: Research and Practice. 4, 1, p. 1-16 16 p., 12.Research output: Contribution to journal › Article › peer-review
Open Access -
Deep learning for anomaly detection in log data: A survey
Landauer, M., Onder, S., Skopik, F. & Wurzenberger, M., 15 Jun 2023, In: Machine Learning with Applications. 12, p. 1-19 19 p., 100470.Research output: Contribution to journal › Article › peer-review
Open Access -
2022
Behavior-Based Anomaly Detection in Log Data of Physical Access Control Systems
Skopik, F., Wurzenberger, M., Höld, G., Landauer, M. & Kuhn, W., 2022, In: IEEE Transactions on Dependable and Secure Computing (TDSC). p. 1-18 18 p.Research output: Contribution to journal › Article › peer-review
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Blind Spots of Security Monitoring in Enterprise Infrastructures: A Survey
Skopik, F., Landauer, M. & Wurzenberger, M., 2022, In: IEEE Security & Privacy. 20, 6, p. 18-26 9 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Dealing with Security Alert Flooding: Using Machine Learning for Domain-independent Alert Aggregation
Landauer, M., Skopik, F., Wurzenberger, M. & Rauber, A., 2022, In: ACM Transactions on Privacy and Security. 25, 18, p. 1-36 36 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Kyoushi Testbed Environment: A Model-driven Simulation Framework to Generate Open Log Data Sets for Security Evaluations
Landauer, M., Skopik, F., Wurzenberger, M. & Hotwagner, W., 2022, In: ERCIM News. 129, 24, p. 24-25 2 p.Research output: Contribution to journal › Article › peer-review
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Maintainable Log Datasets for Evaluation of Intrusion Detection Systems
Landauer, M., Skopik, F., Frank, M., Hotwagner, W., Wurzenberger, M. & Rauber, A., 2022, In: IEEE Transactions on Dependable and Secure Computing. p. 1-17 17 p.Research output: Contribution to journal › Article › peer-review
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Online Log Data Analysis With Efficient Machine Learning: A Review
Skopik, F., Landauer, M. & Wurzenberger, M., 2022, In: IEEE Security & Privacy. 20, 2022, p. 80-90 11 p.Research output: Contribution to journal › Article › peer-review
Open Access -
2021
Enabling exercises, education and research with a comprehensive cyber range
Leitner, M., Frank, M., Langner, G., Landauer, M., Skopik, F., Smith, P., Akhras, B., Hotwagner, W., Kucek, S., Pahi, T., Reuter, L. & Warum, M., 2021, In: Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications (JoWUA). 12, 3, p. 37-61 25 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Have It Your Way: Generating Customized Log Data Sets with a Model-driven Simulation Testbed
Landauer, M., Skopik, F., Wurzenberger, M., Hotwagner, W. & Rauber, A., 2021, In: Transactions on Reliability. 70, p. 402-415 14 p.Research output: Contribution to journal › Article › peer-review
Open Access -
The Seven Golden Principles of Effective Anomaly-Based Intrusion Detection
Skopik, F., Wurzenberger, M. & Landauer, M., 2021, In: IEEE Security & Privacy. 19, p. 36-45 10 p.Research output: Contribution to journal › Article › peer-review
Open Access -
2020
DECEPT: Detecting Cyber-Physical Attacks using Machine Learning on Log Data
Skopik, F., Wurzenberger, M. & Landauer, M., 2020, In: ERCIM News. 123, p. 33-34 2 p.Research output: Contribution to journal › Article › peer-review
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synERGY: Cross-correlation of operational and contextual data to timely detect and mitigate attacks to cyber-physical systems
Skopik, F., Landauer, M., Wurzenberger, M., Vormayr, G., Milosevic, J., Fabini, J., Prüggler, W., Kruschitz, O., Widmann, B., Truckenthanner, K., Rasse, S., Simmer, M. & Zauner, C., 2020, In: Journal of Information Security and Applications. 54, p. 1-23 23 p.Research output: Contribution to journal › Article › peer-review
Open Access -
System Log Clustering Approaches for Cyber Security Applications: A Survey
Landauer, M., Skopik, F., Wurzenberger, M. & Rauber, A., 2020, In: Computers & Security. 92, p. 1-17 17 p.Research output: Contribution to journal › Article › peer-review
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2019
INDICÆTING - Automatically Detecting, Extracting, and Correlating Cyber Threat Intelligence from Raw Computer Log Data
Landauer, M. & Skopik, F., 2019, In: ERCIM News. 116, p. 25-26 2 p.Research output: Contribution to journal › Article › peer-review
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2018
Dynamic Log File Analysis: An Unsupervised Cluster Evolution Approach for Anomaly Detection
Landauer, M., Wurzenberger, M., Skopik, F., Settanni, G. & Filzmoser, P., 2018, In: Computers & Security. 79, p. 94-116 23 p.Research output: Contribution to journal › Article › peer-review