SBA Research is a research center for Information Security funded partly by the national initiative for COMET Competence Centers for Excellent Technologies.
A systematic review of historical and potential applications of fractional derivatives in combination with supervised machine learning. Thus, this article serves to motivate researchers dealing with data-based problems, to be specific machine learning practitioners, to adopt new tools, and enhance their existing approaches. Titel Combining Fractional Derivatives and Supervised Machine… Read More
New paper “Send and Pretend: Exploiting Transcript Consistency Issues in End-to-End Encrypted Group Chats”, was recently accepted for the 35th USENIX Security Symposium. The paper is a collaboration between SBA, the University of Vienna, and the Interdisciplinary Transformation University Austria (IT:U). It was authored by Gabriel K. Gegenhuber, Moritz Grefner, Maximilian Günther, Matthäus Wininger, David Schmidt, and Aljosha Judmayer. ∞
The IRIS web application in version 2.4.26 and possibly others is vulnerable to stored cross-site scripting (XSS) in the assets (CVE-2026-16969), custom attributes (CVE-2026-18360) and datastore upload (CVE-2026-18361) functions. ∞
We are proud to celebrate the outstanding achievements of our researchers, who were recognized at the University of Vienna Faculty of Computer Science's Best-of-the-Best Awards on June 24. ∞