Team

FH-Prof. Dipl.-Ing. Dr. Robert Luh BSc

  • Lecturer
  • Department of Computer Science and Security
Location: B - Campus-Platz 1

Study programmes

  • IT Security (BA)
  • Cyber Security and Resilience (MA)
  • Smart Engineering (BA)
  • Information Security (MA)

Departments

  • Computer Science and Security
  • Media and Digital Technologies

Short profile

  • 1999-2004: Higher Technical School for Economics and Information Technologies Hollabrunn
  • 2008-2011: University of Applied Sciences St. Pölten, BSc IT Security
  • 2011-2013: University of Applied Sciences St. Pölten, Master (Dipl.-Ing.) Information Security
  • Since 2015: PhD student at De Montfort University, Leicester

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Selected Publications

Projects

Publications

Types
From
To
Luh, R. (2022, May 9). PenQuest: Ein Cyber-Abwehr Spiel [Workshop and presentation].
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
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., 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. (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., & Eigner, O. (2019, January 29). Google Hacking. Security Day, FH St. Pölten.
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 4). Mord auf der Festplatte: Ein Ausflug in die digitale Forensik.
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, R., & Eresheim, S. (2018, January 30). Google Hacking. Security Day, FH St. Pölten.
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
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
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
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
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
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., 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
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., 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
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.