Publications

The ubiquitous use of technology by college students makes them vulnerable to harassment, harm, and intimidation via technological means. We evaluate the prevalence of such technology-facilitated abuse (TFA) among college students in the USA using a critical, feminist, and trauma-informed lens, which is essential to inform policymakers and advocates who support students. We surveyed 776 college students in a large R1 university located in the Midwest region of the USA to examine the prevalence of TFA faced by stu- dents marginalized by socio-economic factors, the support sought by student survivors, and the efficacy of support structures. Our findings indicate that 70% students experience TFA, but more than half of them do not seek support. Among the survivors who seek support, 93% students solely rely on informal resources like friends and family, and 6% solely seek support from formal networks such as survivor services or law enforcement. Therefore, we call on policymakers to direct attention to TFA, create tailored interven- tions to support marginalized students and propose campus-wide campaigns to spread awareness among college students

Measured boot is an important class of boot protocols that ensure that each layer of firmware and software in a device’s chain of trust is measured, and the measurements are reliably recorded for subsequent verification. This paper presents DICE*, a formal specification as well as a formally verified implementation of DICE, an industry standard measured boot protocol. DICE* is proved to be functionally correct, memory-safe, and resistant to timing- and cache-based side-channels. A key component of DICE* is a verified certificate creation library for a fragment of X.509. We have integrated DICE* into the boot firmware of an STM32H753ZI micro-controller. Our evaluation shows that using a fully verified implementation has minimal to no effect on the code size and boot time when compared to an existing unverified implementation.

In this paper, we study the effect of instructional priming on postural responses to virtual crowds using a headset-based virtual reality (VR) platform. Specifically, we instruct VR participants that one of the virtual agents in a simulated crowd represents the movement of a real person, and reinforce this instruction by having a single role player present in the experimental arena. Our results show that while VR participants who were primed did not move significantly more when three-dimensional movement was considered, they exhibit significantly more movement in the direction perpendicular to the crowd flow indicating possible collision avoidance maneuvers. These results indicate that manipulation of instructions to participants with the intent of impacting pre-exposure expectations may be used to increase engagement with virtual crowds.

With the advent of the Internet of Things (IoT), privacy and security of sensitive data has become a major concern. In general, sensors which are the enablers for IoT, send the sensed data to a cloud database over the internet. The communication to the cloud database may be compromised by an adversary, or the database maybe accessed by a curious database administrator, thereby raising security concerns. To solve this issue, we demonstrate a solution to safeguard IoT devices in a home network scenario from potential attacks. A firewall is set up using a Raspberry Pi as a gateway which secures their communication with the cloud database. Furthermore, we plan to build a location-aware (physical location in the home network scenario) heuristics and a signature based traffic detection dashboard running on the Raspberry Pi, in order to control the IoT devices and log their network behavior.