Mobile malware impersonates users, penetrates their business organizations through their mobile devices, and locks user data to demand ransom. Detecting malware is challenging even for the most secure application stores, as evident from the recent incidents of malware penetrating the official Android store. In this talk, I will first map the challenges faced by program-analysis-based and machine-learning-based approaches when identifying malicious applications. These include (a) the inability of analysis-based approaches to distinguish between “legitimate” and “illegitimate” code behaviors, (b) their inability to reason about complex, event-driven, and hard-to-trigger application code, and (c) the limited reliability and explainability of machine-learning-based approaches. I will then describe our current work on addressing some of these challenges and will put this work in context of the broader effort of my research group to improve quality, reliability, and security of software and AI-based systems.

Julia Rubin is an Associate Professor in the Department of Electrical and Computer Engineering at the University of British Columbia, Canada. She is a Canada Research Chair in Trustworthy Software and the lead of the UBC Research Excellence Cluster on Trustworthy ML. Julia received her PhD in Computer Science from the University of Toronto and worked as a postdoctoral researcher in CSAIL at MIT. She also spent almost 10 years in industry, working for IBM Research, where she was a Research Staff Member and a Research Group Manager. Julia's research interests are in quality, security, and reliability of software and AI systems. Her work in these areas won 6 Distinguished/Best Paper Awards at major conferences, including ASE and ISSTA. Julia co-chaired Program Committees of several major conferences in her field, such as ASE in 2022, and will co-chair ICSE NIER track in 2025. Her work was also recognized by numerous awards, including CS-Canada Outstanding Early Career Computer Science Researcher Award in 2022 and Killam Faculty Research Fellowship in 2023.