25 citations · 44 across the 7 of their papers we have counts for
11 papers
Re-purposing Perceptual Hashing based Client Side Scanning for Physical Surveillance
Ashish Hooda, Andrey Labunets, Tadayoshi Kohno +1
Content scanning systems employ perceptual hashing algorithms to scan user content for illegal material, such as child pornography or terrorist recruitment flyers. Perceptual hashi…
Exploring Adversarial Robustness of Deep Metric Learning
Thomas Kobber Panum, Zi Wang, Pengyu Kan +2
Deep Metric Learning (DML), a widely-used technique, involves learning a distance metric between pairs of samples. DML uses deep neural architectures to learn semantic embeddings o…
Sequential Attacks on Kalman Filter-based Forward Collision Warning Systems
Yuzhe Ma, Jon Sharp, Ruizhe Wang +2
Kalman Filter (KF) is widely used in various domains to perform sequential learning or variable estimation. In the context of autonomous vehicles, KF constitutes the core component…
Data Privacy in Trigger-Action Systems
Yunang Chen, Amrita Roy Chowdhury, Ruizhe Wang +3
Trigger-action platforms (TAPs) allow users to connect independent web-based or IoT services to achieve useful automation. They provide a simple interface that helps end-users crea…
Invisible Perturbations: Physical Adversarial Examples Exploiting the Rolling Shutter Effect
Athena Sayles, Ashish Hooda, Mohit Gupta +2
Physical adversarial examples for camera-based computer vision have so far been achieved through visible artifacts -- a sticker on a Stop sign, colorful borders around eyeglasses o…
New Problems and Solutions in IoT Security and Privacy
Earlence Fernandes, Amir Rahmati, Nick Feamster
In a previous article for S&P magazine, we made a case for the new intellectual challenges in the Internet of Things security research. In this article, we revisit our earlier obse…