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2019
Ruotsalainen, H., Zhang, J., & Grebeniuk, S. (2019). Experimental Investigation on Wireless Key Generation for Low Power Wide Area Networks. IEEE Internet of Things Journal. https://doi.org/10/ggxwns
Tavolato-Wötzl, C., & Tavolato, P. (2019, February). Analytical Modelling of Cyber-Physical Systems. Proceedings of the 5th International Conference on Information Systems Security and Privacy - ICISSP 2019, 3rd International Workshop on FORmal Methods for Security Engineering - ForSE 2019.
Wenzl, M., Merzdovnik, G., Ullrich, J., & Weippl, E. (2019). From Hack to Elaborate Technique—A Survey on Binary Rewriting. ACM Computing Surveys, 52(3 / Artikel 49). https://doi.org/10.1145/3316415
2018
Amiri, F., Quirchmayr, G., & Kieseberg, P. (2018). A Machine Learning Approach for Privacy-preservation in E-business Applications: Proceedings of the 15th International Joint Conference on E-Business and Telecommunications, 443–452. https://doi.org/10/gh38cd
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.
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
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
2017
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
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
2016
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., 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
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
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
2015
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
2014
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