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Abstract: Mobile systems, including smartphones, wearables, IoT devices, and mixed-reality headsets, have evolved significantly from mere communication tools to sophisticated sensing devices that monitor and control various aspects of our lives. While the advanced computing and sensing capabilities of these devices unlock a myriad of useful applications, they also make them attractive targets for attackers, leading to several security threats and loss of users’ privacy. In this presentation, I will explore the integration of multimodal sensing, computer vision, and machine learning techniques to scrutinize security and privacy threats on emerging computing platforms. Further, I will share insights on improving modern mobile and IoT devices’ security and ensuring users’ privacy. In particular, first, I will demonstrate how human interaction with mobile devices and their accessories (e.g., stylus pencils) generates identifiable patterns that reveal sensitive information about users. Second, I will present multimodal and user-friendly methods for mobile and IoT user and device authentication to enhance the security of these devices. Through this research, the overarching aim is to forge tools and algorithms that empower developers to implement effective and user-friendly solutions addressing the security limitations of both current systems and emerging computing platforms.

Bio: Habiba Farrukh is an Assistant Professor in the Computer Science department at the University of California, Irvine. Prior to joining UCI, Habiba received her Ph.D. at Purdue University, where she was advised by Professor Z. Berkay Celik and was a part of the PurSec Lab. Habiba has conducted research on a variety of topics, including mobile and IoT security and privacy and human-centered computing. Her dissertation focused on leveraging multimodal sensing on mobile and IoT devices to provide rigorous security and privacy guarantees for these systems. She received the Bilsland Fellowship for her dissertation in 2022. She also led a team of graduate students to improve the usability and conformity of Android authorization APIs and the WearOS permission model for the Google ASPIRE (Android Security and PrIvacy REsearch) Award in 2021 and 2022. More information is available at