Publications
- Landauer M., Skopik F., Wurzenberger M., Hotwagner W., Rauber A. (2021): Have It Your Way: Generating Customized Log Data Sets with a Model-driven Simulation Testbed. IEEE Transactions on Reliability, Vol.70, Issue 1, pp. 402-415. IEEE.
- Landauer M., Skopik F., Wurzenberger M., Rauber A. (2020): System Log Clustering Approaches for Cyber Security Applications: A Survey. [pdf] Elsevier Computers & Security Journal, Volume 92. May 2020, pp. 1-17. Elsevier.
- Wurzenberger M., Höld G., Landauer M., Skopik F., Kastner W. (2020): Creating Character-based Templates for Log Data to Enable Security Event Classification.
15th ACM ASIA Conference on Computer and Communications Security (ACM Asia CCS), October 05-09, 2020, Taipei, Taiwan. ACM. - Wurzenberger M., Landauer M., Skopik F., Kastner W. (2019): AECID-PG: A Tree-Based Log Parser Generator To Enable Log Analysis.
4th IEEE/IFIP International Workshop on Analytics for Network and Service Management (AnNet 2019) in conjunction with the IFIP/IEEE International Symposium on Integrated Network Management (IM), April 8, 2019, Washington D.C., USA. IEEE. - Landauer M., Wurzenberger M., Skopik F, Settanni G., Filzmoser P. (2018): Time Series Analysis: Unsupervised Anomaly Detection Beyond Outlier Detection.
14th International Conference on Information Security Practice and Experience (ISPEC), September 25-27, 2018, Tokyo, Japan. Springer LNCS. - Wurzenberger M., Skopik F., Settanni G., Fiedler R. (2018): AECID: A Self-learning Anomaly Detection Approach Based on Light-weight Log Parser Models.
4th International Conference on Information Systems Security and Privacy (ICISSP 2018), January 22-24, 2018, Funchal, Madeira – Portugal. INSTICC - Landauer M., Wurzenberger M., Skopik F., Settanni G., Filzmoser P. (2018): Dynamic Log File Analysis: An Unsupervised Cluster Evolution Approach for Anomaly Detection. [pdf]
Elsevier Computers & Security Journal, Volume 79. November 2018, pp. 94-116. Elsevier. - Wurzenberger M., Skopik F., Landauer M., Greitbauer P., Fiedler R., Kastner W. (2017): Incremental Clustering for Semi-Supervised Anomaly Detection applied on Log Data.
12th International Conference on Availability, Reliability and Security (ARES), August 29 – September 01, 2017, Reggio Calabria, Italy. ACM. - Wurzenberger M., Skopik F., Fiedler R., Kastner W. (2017): Applying High-Performance Bioinformatics Tools for Outlier Detection in Log Data.
3rd IEEE International Conference on Cybernetics (CYBCONF) (CYBCONF), June 21-23, 2017, Exeter, UK. IEEE. - Wurzenberger M., Skopik F., Fiedler R., Kastner W. (2016): Discovering Insider Threats from Log Data with High-Performance Bioinformatics Tools.
8th ACM CCS International Workshop on Managing Insider Security Threats (MIST 2016) colocated with the 23rd ACM Conference on Computer and Communications Security (CCS), October 24-28, 2016, Vienna, Austria. ACM. - Wurzenberger M., Skopik F., Settanni G., Scherrer W. (2016): Complex Log File Synthesis for Rapid Sandbox-Benchmarking of Security- and Computer Network Analysis Tools. [pdf] Elsevier Information Systems (IS), Volume 60, Aug./Sept. 2016, pp. 13-33. Elsevier.
- Friedberg I., Skopik F., Settanni G., Fiedler R. (2015): Combating Advanced Persistent Threats: From Network Event Correlation to Incident Detection [pdf].
Elsevier Computers & Security Journal, Volume 48, pp. 35-57. Elsevier. - Skopik F., Friedberg I., Fiedler R. (2014): Dealing with Advanced Persistent Threats in Smart Grid ICT Networks.
5th IEEE Innovative Smart Grid Technologies Conference, February 19-22, 2014, Washington DC, USA. - Skopik F., Fiedler R. (2013): Intrusion Detection in Distributed Systems using Fingerprinting and Massive Event Correlation.
Jahrestagung der Gesellschaft für Informatik e.V. (GI) (INFORMATIK 2013), September 16-20, 2013, Koblenz, Germany. GI.
Patents
- Landauer M., Skopik F., Wurzenberger M. (2019): EP19153037.7 – Method for detecting anormal operating states) (“Time Series Analysis EP”), European Patent pending, January 2019.
- Wurzenberger M., Landauer M., Skopik F., Fiedler R. (2018): A50461/2018 – Verfahren zur Charakterisierung des Zustands eines Computersystems (“Grammatikerkennung AT”), Austrian Patent pending, June 2018.
- Wurzenberger M., Skopik F. (2018): EP18160444.8 – Method for detecting normal operating states in a working process (“Maschinendatensaetze EP”), European Patent pending, March 2018.
- Landauer M., Skopik F., Wurzenberger M. (2018): A50156/2018 – Verfahren zur Erkennung von anormalen Betriebszuständen (engl.: Method for detecting anormal operating states) (“Time Series Analysis AT”), Austrian Patent pending, February 2018.
- Fiedler R., Skopik F., Wurzenberger M. (2017): EP3267625 – Method for detecting anomolous states in a computer network (“Bioclustering EP”), European Patent granted, September 2018.
- Wurzenberger M., Skopik F. (2017): A50233/2017 – Verfahren zur Erkennung des normalen Betriebszustands eines Arbeitsprozesses (engl.: Method for detecting normal operating states in a working process) (“Maschinendatensaetze AT”), Austrian Patent pending, March 2017.
- Fiedler R., Skopik F., Wurzenberger M. (2016): A50601/2016 (AT 518.805) – Verfahren zur Detektion von anomalen Zuständen in einem Computernetzwerk (engl.: Method for detecting anomolous states in a computer network) (“Bioclustering AT”), Austrian Patent granted, May 2018.
- Skopik F., Fiedler R. (2016): EP 1416597.2-1853 – Method for detecting deviations from a given standard state, June 2016.
- Skopik F., Fiedler R. (2013): A50292/2013 (AT 514.215) – Verfahren zur Feststellung von Abweichungen von einem vorgegebenen Normalzustand, April 2013.)
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