1 citations · 2 across the 5 of their papers we have counts for
5 papers
Err on the Side of Texture: Texture Bias on Real Data
Blaine Hoak, Ryan Sheatsley, Patrick McDaniel
Bias significantly undermines both the accuracy and trustworthiness of machine learning models. To date, one of the strongest biases observed in image classification models is text…
ParTEETor: A System for Partial Deployments of TEEs within Tor
Rachel King, Quinn Burke, Yohan Beugin +5
The Tor anonymity network allows users such as political activists and those under repressive governments to protect their privacy when communicating over the internet. At the same…
Explorations in Texture Learning
Blaine Hoak, Patrick McDaniel
In this work, we investigate \textit{texture learning}: the identification of textures learned by object classification models, and the extent to which they rely on these textures.…
Systematic Evaluation of Geolocation Privacy Mechanisms
Alban Héon, Ryan Sheatsley, Quinn Burke +4
Location data privacy has become a serious concern for users as Location Based Services (LBSs) have become an important part of their life. It is possible for malicious parties hav…
Privacy-Preserving Protocols for Smart Cameras and Other IoT Devices
Yohan Beugin, Quinn Burke, Blaine Hoak +5
Millions of consumers depend on smart camera systems to remotely monitor their homes and businesses. However, the architecture and design of popular commercial systems require user…