Publikationen: Institut für IT Sicherheitsforschung – FHSTP

Holzinger, A., Kieseberg, P., Weippl, E., & Tjoa, A. M. (2018). Current Advances, Trends and Challenges of Machine Learning and Knowledge Extraction: From Machine Learning to Explainable AI. In A. Holzinger, P. Kieseberg, A. M. Tjoa, & E. Weippl (Eds.), Machine Learning and Knowledge Extraction (Vol. 11015, pp. 1–8). Springer International Publishing. https://doi.org/10.1007/978-3-319-99740-7_1

Goebel, R., Chander, A., Holzinger, K., Lecue, F., Akata, Z., Stumpf, S., Kieseberg, P., & Holzinger, A. (2018). Explainable AI: The New 42? In A. Holzinger, P. Kieseberg, A. M. Tjoa, & E. Weippl (Eds.), Machine Learning and Knowledge Extraction (Vol. 11015, pp. 295–303). Springer International Publishing. https://doi.org/10.1007/978-3-319-99740-7_21

CD-MAKE. (2018). Machine learning and knowledge extraction: Second IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12.9, International Cross-Domain Conference, CD-MAKE 2018, Hamburg, Germany, August 27–30, 2018: proceedings (A. Holzinger, P. Kieseberg, A. M. Tjoa, & E. R. Weippl, Eds.). Springer.

Bibtex

Kieseberg, P., Schrittwieser, S., & Weippl, E. (2018). Structural Limitations of B+-Tree forensics. Proceedings of the Central European Cybersecurity Conference 2018 on - CECC 2018, 1–4. https://doi.org/10/gh372c

Kubler, S., Robert, J., Neumaier, S., Umbrich, J., & Le Traon, Y. (2018). Comparison of metadata quality in open data portals using the Analytic Hierarchy Process. Government Information Quarterly, 35(1), 13–29. https://doi.org/10/gdbpvg

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

Bibtex

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

Bibtex

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

Bibtex

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

Neumaier, S., Umbrich, J., & Polleres, A. (2016). Automated Quality Assessment of Metadata across Open Data Portals. ACM Journal of Data and Information Quality (JDIQ), Journal of Data and Information QualityVolume 8Issue 1(Journal of Data and Information QualityVolume 8Issue 1), pp 1-29. https://doi.org/https://doi.org/10.1145/2964909

Neumaier, S., Umbrich, J., Parreira, J. X., & Polleres, A. (2016). Multi-level Semantic Labelling of Numerical Values. The Semantic Web – ISWC 2016, 428–445. https://link.springer.com/chapter/10.1007/978-3-319-46523-4_26

Schrittwieser, S., Katzenbeisser, S., Kinder, J., Merzdovnik, G., & Weippl, E. (2016). Protecting software through obfuscation: Can it keep pace with progress in code analysis. Computing Surveys, 49(1). https://doi.org/10/gftfv5

Bibtex

Priebe, T., & Markus, S. (2015). Business Information Modeling: A Methodology for Data-Intensive Projects, Data Science and Big Data Governance. 2015 IEEE International Conference on Big Data (Big Data), IEEE, 2056–2065. https://doi.org/10.1109/BigData.2015.7363987

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

Priebe, T., Reisser, A., & Hoang, D. T. A. (2011). Reinventing the Wheel?! Why Harmonization and Reuse Fail in Complex Data Warehouse Environments and a Proposed Solution to the Problem. 10. Internationale Tagung Wirtschaftsinformatik (WI 2011), Zürich. https://aisel.aisnet.org/wi2011/38