Team

Dipl.-Ing. Dr. Robert Luh BSc

  • FH-Dozent
  • Department Informatik und Security
Arbeitsplatz: D - Heinrich Schneidmadl-Straße 15

Studiengänge

  • IT Security (BA)
  • Information Security (MA)

Departments

  • Informatik und Security

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

Download CV

Ausgewählte Publikationen

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/10.1007/s11416-018-0318-x
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.

Projekte

Publikationen

Typen
Von
Bis
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/10.1007/s11416-019-00342-x
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/https://doi.org/10.1016/j.cose.2019.03.015
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., 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/10.1007/s11416-018-0318-x
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.
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.
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/10.1109/ICSSA.2017.17
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/10.2197/ipsjjip.25.866
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.
Luh, R., Schrittwieser, S., & Marschalek, S. (2017). LLR-based Sentiment Analysis for Kernel Event Sequences. 31th International Conference on Advanced Information Networking and Applications.
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., 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.
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/10.1145/3078861.3084162
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.
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/10.1007/s11416-016-0273-3
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/10.1145/2872518.2888609
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).
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).
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/10.2312/eurovisstar.20151114
Haslinger, D., & Luh, R. (2015, September 30). Alltagsspuren von dir und mir. 6. Science Day.
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/10.1145/2671491.2671498
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.