Publikationen
Gefiltert nach:
Sortierung nach Jahr und AutorInnen
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. https://link.springer.com/book/10.1007/978-3-030-29726-8
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., 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., & Schrittwieser, S. (2019). Advanced threat intelligence: detection and classification of anomalous behavior in system processes. E \& i Elektrotechnik Und Informationstechnik, Springer, 1–7.
Neumaier, S., & Polleres, A. (2019). Enabling Spatio-Temporal Search in Open Data. Journal of Web Semantics, 55(Elsevier), 21–36. https://doi.org/10/ggwb56
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
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.
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