#Malware Analysis
The analysis of malware improves IT security, protects privacy and supports the defence against IT attacks.
Publications
Dahnert, M., Rind, A., Aigner, W., & Kehrer, J. (2019). Looking beyond the horizon: Evaluation of four compact visualization techniques for time series in a spatial context. ArXiv:1906.07377 [Cs].
Rind, A., Wagner, M., & Aigner, W. (2019). Towards a Structural Framework for Explicit Domain Knowledge in Visual Analytics. In Proc. Workshop on Visual Analytics in Healthcare (VAHC 2019).
Wagner, M., Slijepcevic, D., Horsak, B., Rind, A., Zeppelzauer, M., & Aigner, W. (2018). KAVAGait: Knowledge-Assisted Visual Analytics for Clinical Gait Analysis. IEEE Transactions on Visualization and Computer Graphics (TVCG), 25(3), 1528–1542. https://doi.org/10.1109/TVCG.2017.2785271
Aigner, W., Rind, A., & Wagner, M. (2018). KAVA-Time: Knowledge-Assisted Visual Analytics Methods for Time-Oriented Data. In Tagungsband des 12. Forschungsforum der österreichischen Fachhochschulen (FFH) 2018.
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
Bernard, J., Zeppelzauer, M., Sedlmair, M., & Aigner, W. (2018). VIAL – A Unified Process for Visual-Interactive Labeling. The Visual Computer, 34(1189), 16. https://doi.org/10.1007/s00371-018-1500-3
Andrienko, N., Lammarsch, T., Andrienko, G., Fuchs, G., Keim, D. A., Miksch, S., & Rind, A. (2018). Viewing Visual Analytics as Model Building. Computer Graphics Forum, 37(6), 275–299. https://doi.org/10.1111/cgf.13324
Rind, A., Iber, M., & Aigner, W. (2018). Bridging the Gap Between Sonification and Visualization. In Proc. AVI Workshop on Multimodal Interaction for Data Visualization (MultimodalVis).
Luh, Robert, Temper, M., Tjoa, S., & Schrittwieser, S. (2018). APT RPG: Design of a Gamified Attacker/Defender Meta Model. In 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. In Proceedings of the 10th Forum Media Technology 2017 (pp. 107–115). St. Pölten: CEUR-WS.