ECE 469/569 - Mobile & Embedded System Security / Fall 2024
Course Description
Introduction to vulnerabilities and threat vectors associated with mobile and embedded devices, such as smartphones, wearable devices, and IoT devices, and the potential security and privacy issues associated with machine learning models deployed on mobile and IoT devices. Topics include security features and limitations of intelligent audio systems (e.g., voice assistants), user authentication/verification, trustworthy and robust machine learning models (e.g., adversarial attacks, backdoor attacks, and privacy-preserving federated learning), side-channel attacks on mobile/wearable devices, acoustic sensing for security, and security and privacy breaches via inertial sensors on smart home devices. The coursework focuses on enhancing students' understanding and awareness of security and privacy concerns in mobile and embedded systems, as well as machine learning models operating within them, through individual homework&programming assignments and an intensive final project involving hands-on research.
Meeting Time and Office Hours
Lectures: MWF 10:20AM-11:10AM (MKB-405)
Office Hours:
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Instructor: by appointment (Office: MKB-307)
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GTA - Kyungchan Lim: 1-2 PM every Wednesday (Office: MKB 339)
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GTA - Syed Irfan Ali Meerza: 1-2 PM every Thursday (Office: MKB 630)
Slack Workspace
Join our Slack Workspace to stay updated with course notifications while engaging in vibrant discussions.
I highly encourage you to use this platform not only for asking questions but also to engage in collaborative learning experiences with your peers, where you can share insights and participate in meaningful discussions about the course materials and related topics.
