activity
20182025
most citedHow To Backdoor Federated Learning

808 citations · 1.1k across the 21 of their papers we have counts for

collaborators

22 papers

cs.AI2025

Throttling Web Agents Using Reasoning Gates

Abhinav Kumar, Jaechul Roh, Ali Naseh +2

AI web agents use Internet resources at far greater speed, scale, and complexity -- changing how users and services interact. Deployed maliciously or erroneously, these agents coul…

cs.CR2025

Network-Level Prompt and Trait Leakage in Local Research Agents

Hyejun Jeong, Mohammadreza Teymoorianfard, Abhinav Kumar +2

We show that Web and Research Agents (WRAs) -- language-model-based systems that investigate complex topics on the Internet -- are vulnerable to inference attacks by passive networ…

cs.AI2025

Privacy Reasoning in Ambiguous Contexts

Ren Yi, Octavian Suciu, Adria Gascon +3

We study the ability of language models to reason about appropriate information disclosure - a central aspect of the evolving field of agentic privacy. Whereas previous works have…

cs.CR2025

Can Large Language Models Really Recognize Your Name?

Dzung Pham, Peter Kairouz, Niloofar Mireshghallah +3

Large language models (LLMs) are increasingly being used in privacy pipelines to detect and remedy sensitive data leakage. These solutions often rely on the premise that LLMs can r…

cs.LG2025

OverThink: Slowdown Attacks on Reasoning LLMs

Abhinav Kumar, Jaechul Roh, Ali Naseh +4

A reasoning language model (RLM) generates costly reasoning tokens, often hidden from the users, that help it excel at many tasks. Our Overthink attack targets RLM-based applicatio…

cs.CR2025

Firewalls to Secure Dynamic LLM Agentic Networks

Sahar Abdelnabi, Amr Gomaa, Eugene Bagdasarian +2

The emergence of agent-to-agent communication protocols mirrors the early internet: powerful connectivity with minimal security infrastructure. When AI agents communicate on behalf…