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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

LEVERAGING MULTIMODAL SENSING FOR ENHANCING THE SECURITY AND PRIVACY OF MOBILE SYSTEMS

Habiba Farrukh (13969653) 26 July 2023 (has links)
<p>Mobile systems, such as smartphones, wearables (e.g., smartwatches, AR/VR headsets),<br> and IoT devices, have come a long way from being just a method of communication to<br> sophisticated sensing devices that monitor and control several aspects of our lives. These<br> devices have enabled several useful applications in a wide range of domains ranging from<br> healthcare and finance to energy and agriculture industries. While such advancement has<br> enabled applications in several aspects of human life, it has also made these devices an<br> interesting target for adversaries.<br> In this dissertation, I specifically focus on how the various sensors on mobile devices can<br> be exploited by adversaries to violate users’ privacy and present methods to use sensors<br> to improve the security of these devices. My thesis posits that multi-modal sensing can be<br> leveraged to enhance the security and privacy of mobile systems.<br> In this, first, I describe my work that demonstrates that human interaction with mobile de-<br> vices and their accessories (e.g., stylus pencils) generates identifiable patterns in permissionless<br> mobile sensors’ data, which reveal sensitive information about users. Specifically, I developed<br> S3 to show how embedded magnets in stylus pencils impact the mobile magnetometer sensor<br> and can be exploited to infer a users incredibly private handwriting. Then, I designed LocIn<br> to infer a users indoor semantic location from 3D spatial data collected by mixed reality<br> devices through LiDAR and depth sensors. These works highlight new privacy issues due to<br> advanced sensors on emerging commodity devices.<br> Second, I present my work that characterizes the threats against smartphone authentication<br> and IoT device pairing and proposes usable and secure methods to protect against these threats.<br> I developed two systems, FaceRevelio and IoTCupid, to enable reliable and secure user and<br> device authentication, respectively, to protect users’ private information (e.g., contacts,<br> messages, credit card details) on commodity mobile and allow secure communication between<br> IoT devices. These works enable usable authentication on diverse mobile and IoT devices<br> and eliminate the dependency on sophisticated hardware for user-friendly authentication.</p>

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