FH-Prof. Dipl.-Ing. Dr. Robert Luh BSc
- Studiengangsleiter IT Security (BA)
- Department Informatik und Security
Studiengänge
- IT Security (BA)
- Smart Engineering (BA)
- Cyber Security and Resilience (MA)
- Information Security (MA)
Departments
- Informatik und Security
- Medien und Digitale Technologien
Kurzprofil
- 1999-2004: HTL für Wirtschaftsingenieurwesen, Hollabrunn
- 2005-2006: Internationales Projekt bei Nestlé Zone Europe Purchasing
- 2006-2008: IT Administration bei First Data
- 2008-2011: Studium der IT Security (BSc) an der FH St. Pölten
- 2011-2013: Studium der Information Security (DI) an der FH St. Pölten
- 2015-2019: Dissertation an der De Montfort University Leicester
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Projekte
Ausgewählte Publikationen
Publikationen
Tavolato, P., Luh, R., & Eresheim, S. (2023). A Game Theoretic Analysis of Cyber Threats: Proceedings of the 9th International Conference on Information Systems Security and Privacy, 706–713. https://doi.org/10.5220/0011792700003405
Luh, R. (2022, November 29). PenQuest: A Digital Cyber Defense Game for Higher Education [Workshop and presentation].
Luh, R., Eresheim, S., Größbacher, S., Petelin, T., Mayr, F., Tavolato, P., & Schrittwieser, S. (2022). PenQuest Reloaded: A Digital Cyber Defense Game for Technical Education. 2022 IEEE Global Engineering Education Conference (EDUCON), 906–914. https://doi.org/10.1109/EDUCON52537.2022.9766700
Boigner, P., & Luh, R. (2022). WSL2 Forensics: Detection, Analysis & Revirtualization. The 17th International Conference on Availability, Reliability and Security. https://doi.org/https://doi.org/10.1145/3538969.3544439
Luh, R. (2021, July 20). PenQuest: An adversarial cyber security game for education and threat assessment (ext.). Research seminar, University of Luxembourg (remote).
Luh, R. (2021, May 13). PenQuest: An adversarial cyber security game for education and threat assessment. Research seminar, Massachusetts Institute of Technology (remote). https://calendar.csail.mit.edu/events/235459
Galhuber, M., & Luh, R. (2021). Time for Truth: Forensic Analysis of NTFS Timestamps. The 16th International Conference on Availability, Reliability and Security. https://doi.org/10/gnhmbb
Luh, R., & Schrittwieser, S. (2019). Advanced threat intelligence: detection and classification of anomalous behavior in system processes. E \& i Elektrotechnik Und Informationstechnik, Springer, 1–7.
Luh, R., Temper, M., Tjoa, S., Schrittwieser, S., & Janicke, H. (2019). PenQuest: a gamified attacker/defender meta model for cyber security assessment and education. Journal of Computer Virology and Hacking Techniques. https://doi.org/10/gh378z
Luh, R. (2019). Advanced Threat Intelligence: Interpretation of Anomalous Behavior in Ubiquitous Kernel Processes [Dissertation]. De Monfort University Leicester. https://dora.dmu.ac.uk/handle/2086/18527
Luh, R., Janicke, H., & Schrittwieser, S. (2019). AIDIS: Detecting and classifying anomalous behavior in ubiquitous kernel processes. Computers & Security, 84, 120–147. https://doi.org/10/gh38cc
Luh, R. (2018, June 20). PenQuest: Attacker/Defender Educational Game. Studiengangsbeirat, Fachhochschule St. Pölten.
Luh, R. (2018, January 5). From murder to malware: Digital forensics for treasure hunters. FH Kiel, FH Kiel.
Schrittwieser, S., & Luh, R. (2018, April 13). Mord im Planetarium - Ein Ausflug in die Welt der Digitalen Forensik. Volkshochschule Wien, Wien.
Luh, R. (2018, January 3). Malware Analysis. De Montfort University Leicester, De Montfort University Leicester.
Luh, R. (2018). Fragen an die Wissenschaft: Warum werden Datenbestände immer größer? Niederösterreichische Nachrichten.
Luh, Robert, Temper, M., Tjoa, S., & Schrittwieser, S. (2018). APT RPG: Design of a Gamified Attacker/Defender Meta Model. International Workshop on FORmal Methods for Security Engineering. International Workshop on FORmal methods for Security Engineering.
Luh, R., Schramm, G., Wagner, M., Janicke, H., & Schrittwieser, S. (2018). SEQUIN: a grammar inference framework for analyzing malicious system behavior. Journal of Computer Virology and Hacking Techniques, 01–21. https://doi.org/10/cwdf
Rauchberger, J., Schrittwieser, S., Dam, T., Luh, R., Buhov, D., Pötzelsberger, G., & Kim, H. (2018). The Other Side of the Coin: A Framework for Detecting and Analyzing Web-based Cryptocurrency Mining Campaigns. Proceedings of the 13th International Conference on Availability, Reliability and Security. ARES 2018, Hamburg, Deutschland. https://doi.org/10/gh373c
Thür, N., Wagner, M., Schick, J., Niederer, C., Eckel, J., Luh, R., & Aigner, W. (2017). A Bigram Supported Generic Knowledge-Assisted Malware Analysis System: BiG2-KAMAS. Proceedings of the 10th Forum Media Technology 2017, 107–115. http://mc.fhstp.ac.at/sites/default/files/publications/Thuer_B2KAMAS_2017.pdf
Thür, N., Wagner, M., Schick, J., Niederer, C., Eckel, J., Luh, R., & Aigner, W. (2017). BiG2-KAMAS: Supporting Knowledge-Assisted Malware Analysis with Bi-Gram Based Valuation. Poster of the 14th Workshop on Visualization for Cyber Security (VizSec). http://mc.fhstp.ac.at/sites/default/files/publications/vizsec-poster-2017%20%281%29.pdf
Marschalek, S., Luh, R., & Schrittwieser, S. (2017). Endpoint Data Classification Using Markov Chains. 2017 International Conference on Software Security and Assurance (ICSSA), 56–59. https://doi.org/10/gnt2tz
Luh, R., Schrittwieser, S., Marschalek, S., Janicke, H., & Weippl, E. (2017). Design of an Anomaly-based Threat Detection & Explication System. 22nd ACM Symposium on Access Control Models and Technologies (SACMAT). https://doi.org/10/gnd63p
Luh, R., Schrittwieser, S., Janicke, H., & Marschalek, S. (2017). Design of an Anomaly-based Threat Detection & Explication System. Third International Conference on Information Systems Security and Privacy, Madeira, Portugal. https://doi.org/10/gnd7mx
Rauchberger, J., Luh, R., & Schrittwieser, S. (2017). Longkit - A Universal Framework for BIOS/UEFI Rootkits in System Management Mode. Third International Conference on Information Systems Security and Privacy, Madeira, Portugal. https://doi.org/10/gh3729
Luh, R., Schrittwieser, S., & Marschalek, S. (2017). LLR-based Sentiment Analysis for Kernel Event Sequences. 31th International Conference on Advanced Information Networking and Applications. https://doi.org/10/gh3728
Eresheim, S., Luh, R., & Schrittwieser, S. (2017). The Evolution of Process Hiding Techniques in Malware – Current Threats and Possible Countermeasures. Journal of Information Processing. https://doi.org/10/gh3722
Wagner, M., Sacha, D., Rind, A., Fischer, F., Luh, R., Schrittwieser, S., Keim, D. A., & Aigner, W. (2017). Visual Analytics: Foundations and Experiences in Malware Analysis. In L. B. Othmane, M. G. Jaatun, & E. Weippl (Eds.), Empirical Research for Software Security: Foundations and Experience (pp. 139–171). CRC/Taylor and Francis.
Luh, R., Schramm, G., Wagner, M., & Schrittwieser, S. (2017). Sequitur-based Inference and Analysis Framework for Malicious System Behavior. First International Workshop on Formal Methods for Security Engineering. https://doi.org/10/cwdb
Luh, R., Schrittwieser, S., & Marschalek, S. (2016). TAON: An Ontology-based Approach to Mitigating Targeted Attacks. International Conference on Information Integration and Web-based Applications & Services (iiWAS). https://doi.org/10/gnt2tw
Marschalek, S., Kaiser, M., Luh, R., & Schrittwieser, S. (2016). Empirical Malware Research through Observation of System Behaviour. First Workshop on Empirical Research Methods in Information Security, 467–469. https://doi.org/10/gnt2tx
Luh, R., Marschalek, S., Kaiser, M., Janicke, H., & Schrittwieser, S. (2016). Semantics-aware detection of targeted attacks – A survey. Journal of Computer Virology and Hacking Techniques, 1–39. https://doi.org/10/gh372z
Haslinger, D., & Luh, R. (2015, September 30). Alltagsspuren von dir und mir. 6. Science Day.
Wagner, M., Fischer, F., Luh, R., Haberson, A., Rind, A., Keim, D. A., & Aigner, W. (2015). A Survey of Visualization Systems for Malware Analysis. In R. Borgo, F. Ganovelli, & I. Viola (Eds.), Eurographics Conference on Visualization (EuroVis) - STARs (pp. 105–125). The Eurographics Association. https://doi.org/10/cwc4
Marschalek, S., Luh, R., Kaiser, M., & Schrittwieser, S. (2015). Classifying Malicious System Behavior using Event Propagation Trees. Proceedings of the 17th International Con- Ference on Information Integration and Web-Based Applications Services (IiWAS2015). https://doi.org/10/gh378f
Wagner, M., Aigner, W., Rind, A., Dornhackl, H., Kadletz, K., Luh, R., & Tavolato, P. (2014). Problem Characterization and Abstraction for Visual Analytics in Behavior-Based Malware Pattern Analysis. In L. Harrison (Ed.), Proceedings of the Eleventh Workshop on Visualization for Cyber Security (pp. 9–16). ACM. https://doi.org/10/cv8p
Luh, R., & Tavolato, P. (2012). Behavior-Based Malware Recognition. 6. Forschungsforum Der Österreichischen Fachhochschulen - Tagungsband 1 Informationstechnologie Als Produktionsfaktor, 79–84.
Luh, R., & Tavolato, P. (2011). Automatische verhaltensbasierte Malware-Analyse. Hackin9, 11.