75 citations · 242 across the 12 of their papers we have counts for
11 papers · 1 filter
SALSA VERDE: a machine learning attack on Learning With Errors with sparse small secrets
Cathy Yuanchen Li, Emily Wenger, Zeyuan Allen-Zhu +2
Learning with Errors (LWE) is a hard math problem used in post-quantum cryptography. Homomorphic Encryption (HE) schemes rely on the hardness of the LWE problem for their security,…
SALSA PICANTE: a machine learning attack on LWE with binary secrets
Cathy Li, Jana Sotáková, Emily Wenger +4
Learning with Errors (LWE) is a hard math problem underpinning many proposed post-quantum cryptographic (PQC) systems. The only PQC Key Exchange Mechanism (KEM) standardized by NIS…
Glaze: Protecting Artists from Style Mimicry by Text-to-Image Models
Shawn Shan, Jenna Cryan, Emily Wenger +3
Recent text-to-image diffusion models such as MidJourney and Stable Diffusion threaten to displace many in the professional artist community. In particular, models can learn to mim…
Data Isotopes for Data Provenance in DNNs
Emily Wenger, Xiuyu Li, Ben Y. Zhao +1
Today, creators of data-hungry deep neural networks (DNNs) scour the Internet for training fodder, leaving users with little control over or knowledge of when their data is appropr…
SALSA: Attacking Lattice Cryptography with Transformers
Emily Wenger, Mingjie Chen, François Charton +1
Currently deployed public-key cryptosystems will be vulnerable to attacks by full-scale quantum computers. Consequently, "quantum resistant" cryptosystems are in high demand, and l…
Post-breach Recovery: Protection against White-box Adversarial Examples for Leaked DNN Models
Shawn Shan, Wenxin Ding, Emily Wenger +2
Server breaches are an unfortunate reality on today's Internet. In the context of deep neural network (DNN) models, they are particularly harmful, because a leaked model gives an a…
Assessing Privacy Risks from Feature Vector Reconstruction Attacks
Emily Wenger, Francesca Falzon, Josephine Passananti +2
In deep neural networks for facial recognition, feature vectors are numerical representations that capture the unique features of a given face. While it is known that a version of…
SoK: Anti-Facial Recognition Technology
Emily Wenger, Shawn Shan, Haitao Zheng +1
The rapid adoption of facial recognition (FR) technology by both government and commercial entities in recent years has raised concerns about civil liberties and privacy. In respon…
"Hello, It's Me": Deep Learning-based Speech Synthesis Attacks in the Real World
Emily Wenger, Max Bronckers, Christian Cianfarani +4
Advances in deep learning have introduced a new wave of voice synthesis tools, capable of producing audio that sounds as if spoken by a target speaker. If successful, such tools in…
Blacklight: Scalable Defense for Neural Networks against Query-Based Black-Box Attacks
Huiying Li, Shawn Shan, Emily Wenger +3
Deep learning systems are known to be vulnerable to adversarial examples. In particular, query-based black-box attacks do not require knowledge of the deep learning model, but can…
Fawkes: Protecting Privacy against Unauthorized Deep Learning Models
Shawn Shan, Emily Wenger, Jiayun Zhang +3
Today's proliferation of powerful facial recognition systems poses a real threat to personal privacy. As Clearview.ai demonstrated, anyone can canvas the Internet for data and trai…