Temple University 3 credits CIS
Mobile and embedded devices, ranging from smartphones and smartwatches to AR/VR headsets, have become extensions of the human user due to their powerful onboard computing and rich sensing capabilities. Unlike traditional mobile endpoints, these devices host third-party applications and continuously collect highly sensitive user data, including biometrics, location, and physical activities, creating unique attack surfaces. The objective of this course is to explore the security architectures and privacy challenges inherent to these user-centric mobile and embedded systems. The course focuses on identifying risks in the interaction between hardware, the OS, and the application layer. Students will learn to examine the internal security models of modern mobile operating systems (e.g., Android, iOS) and the vulnerabilities introduced by embedded sensors, analyze security vulnerabilities of mobile applications, design defense mechanisms against sensor-based side-channel attacks, and assess privacy risks in emerging wearable technologies. The topics of this course will cover: Mobile OS Security Models, Mobile Application Security, Sensor-Based Threats and Privacy, Hardware-Assisted Security, Emerging Interface Security, and AI-Driven Application Security. In addition to individual assignments, students will participate in an intensive group project that involves researching, developing, and experimentally validating a security mechanism or vulnerability on a mobile/embedded platform.
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