54 citations · 59 across the 7 of their papers we have counts for
6 papers · 1 filter
RATION: Towards Quantitative Risk-Based Access Control for AI Agents
Yuntao Du, Harsh Chaudhari, Yuetian Chen +8
AI agents increasingly interact with external environments to complete complex user tasks. These interactions can lead to unexpected behavior and expose agents to security threats…
BrowseSafe++: Benchmarking Prompt Injection Detection Across Web Contexts, Languages, and Browser Views
Yuetian Chen, Kaiyuan Zhang, Yuntao Du +6
Browser agents need to make decisions and execute actions on behalf of users while consuming untrusted webpages, creating opportunities for malicious instructions embedded in webpa…
Privacy Leakage from a Thousand Words: Millipixel Location Recovery from Dot Maps
Yuntao Du, Tanishq Pauskar, Hao Wang +2
Dot maps, which visualize individual data points as dots over a geographic region, are widely used across diverse domains to represent spatial patterns in sensitive data. However,…
Cascading and Proxy Membership Inference Attacks
Yuntao Du, Jiacheng Li, Yuetian Chen +5
A Membership Inference Attack (MIA) assesses how much a trained machine learning model reveals about its training data by determining whether specific query instances were included…
The Federation Strikes Back: A Survey of Federated Learning Privacy Attacks, Defenses, Applications, and Policy Landscape
Joshua C. Zhao, Saurabh Bagchi, Salman Avestimehr +7
Deep learning has shown incredible potential across a wide array of tasks, and accompanied by this growth has been an insatiable appetite for data. However, a large amount of data…
MIST: Defending Against Membership Inference Attacks Through Membership-Invariant Subspace Training
Jiacheng Li, Ninghui Li, Bruno Ribeiro
In Member Inference (MI) attacks, the adversary try to determine whether an instance is used to train a machine learning (ML) model. MI attacks are a major privacy concern when usi…