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Priebe, T., Neumaier, S., & Markus, S. (2021). Finding Your Way Through the Jungle of Big Data Architectures. 2021 IEEE International Conference on Big Data (Big Data), Orlando, FL, USA.
Slijepčević, D., Henzl, M., Klausner, L. D., Dam, T., Kieseberg, P., & Zeppelzauer, M. (2021). k‑Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers. Computers & Security, 111, 19.
Stöger, K., Schneeberger, D., Kieseberg, P., & Holzinger, A. (2021). Legal aspects of data cleansing in medical AI. Computer Law & Security Review, 42.
Holzinger, A., Kieseberg, P., & Müller, H. (2020). KANDINSKY Patterns: A Swiss-Knife for the Study of Explainable AI. ERCIM-News, 120, 41–42.
Holzinger, A., Kieseberg, P., Tjoa, A. M., & Weippl, E. (2020). Machine Learning and Knowledge Extraction: Fourth IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE 2020. Springer.
Longo, L., Goebel, R., Lecue, F., Kieseberg, P., & Holzinger, A. (2020, August 27). Explainable Artificial Intelligence: Concepts, Applications, Research Challenges and Visions. International Cross-Domain Conference for Machine Learning and Knowledge Extraction, Virtuell.
Pellegrini, T., Blomqvist, E., Groth, P., de Boer, V., Alam, M., Käfer, T., Kieseberg, P., Kirrane, S., Meroño-Peñuela, A., & Pandit, H. J. (Eds.). (2020). Semantic Systems. In the Era of Knowledge Graphs: 16th International Conference on Semantic Systems, SEMANTiCS 2020, Amsterdam, The Netherlands, September 7–10, 2020, Proceedings (Vol. 12378). Springer International Publishing.
Schacht, B., & Kieseberg, P. (2020). An Analysis of 5 Million OpenPGP Keys. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications (JoWUA), 11(3), 107–140.
Told, J., & Neumaier, S. (2020). Willensbildung der Kapitalgesellschafter in absentia. Wirtschaftsrechtliche Blätter, 34(7), 361–375.
Weber, T., Mitöhner, J., Neumaier, S., & Polleres, A. (2020). ODArchive – Creating an Archive for Structured Data from Open Data Portals. In J. Z. Pan, V. Tamma, C. d"Amato, K. Janowicz, B. Fu, A. Polleres, O. Seneviratne, & L. Kagal (Eds.), The Semantic Web – ISWC 2020 (pp. 311–327). Springer International Publishing.
Amiri, F., Quirchmayr, G., Kieseberg, P., Bertone, A., & Weippl, E. (2019). Efficiently Vectorized Anonymization in Data Mining using Genetic Algorithms. Proceedings of the 34th International Conference on ICT Systems Security and Privacy Protection-IFIP SEC 2019.
Holzinger, A., Kieseberg, P., Tjoa, A. M., & Weippl, E. (2019). Machine Learning and Knowledge Extraction: Third IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE 2019. Springer.
Kreimel, P., & Tavolato, P. (2019, December 9). Neural Net-Based Anomaly Detection System in Substation Networks. 6th International Symposium for ICS & SCADA Cyber Security Research, Athen, Griechenland.
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., Janicke, H., & Schrittwieser, S. (2019). AIDIS: Detecting and classifying anomalous behavior in ubiquitous kernel processes. Computers & Security, 84, 120–147.
Neumaier, S., & Polleres, A. (2019). Enabling Spatio-Temporal Search in Open Data. Journal of Web Semantics, 55(Elsevier), 21–36.
Ruotsalainen, H., Zhang, J., & Grebeniuk, S. (2019). Experimental Investigation on Wireless Key Generation for Low Power Wide Area Networks. IEEE Internet of Things Journal.
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).
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.