<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>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/23739489 |
| Date | 26 July 2023 |
| Creators | Habiba Farrukh (13969653) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/LEVERAGING_MULTIMODAL_SENSING_FOR_ENHANCING_THE_SECURITY_AND_PRIVACY_OF_MOBILE_SYSTEMS/23739489 |
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