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

  • FH-Dozent
  • Department Informatik und Security
Arbeitsplatz: B - Campus-Platz 1

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

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Projekte

Ausgewählte Publikationen

Publikationen

Typen
Von
Bis
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., & 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.
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
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, 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
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.
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
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
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
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.
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., 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
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.