98 citations · 282 across the 36 of their papers we have counts for
7 papers · 1 filter
STAR-FL: Secure Federated Learning with Spatial-Temporal Analysis and Robust Aggregation
Nawrin Tabassum, Yanzhao Wu
Data poisoning attacks pose serious security threats to Federated Learning (FL) systems in Computer Vision. Despite growing research attention, two key challenges remain for existi…
What Hard Tokens Reveal: Exploiting Low-confidence Tokens for Membership Inference Attacks against Large Language Models
Md Tasnim Jawad, Mingyan Xiao, Yanzhao Wu
With the widespread adoption of Large Language Models (LLMs) and increasingly stringent privacy regulations, protecting data privacy in LLMs has become essential, especially for pr…
Multi-turn Jailbreaking Attack in Multi-Modal Large Language Models
Badhan Chandra Das, Md Tasnim Jawad, Joaquin Molto +2
In recent years, the security vulnerabilities of Multi-modal Large Language Models (MLLMs) have become a serious concern in the Generative Artificial Intelligence (GenAI) research.…
System Prompt Extraction Attacks and Defenses in Large Language Models
Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu
The system prompt in Large Language Models (LLMs) plays a pivotal role in guiding model behavior and response generation. Often containing private configuration details, user roles…
On the Efficiency of Privacy Attacks in Federated Learning
Nawrin Tabassum, Ka-Ho Chow, Xuyu Wang +2
Recent studies have revealed severe privacy risks in federated learning, represented by Gradient Leakage Attacks. However, existing studies mainly aim at increasing the privacy att…
STDLens: Model Hijacking-Resilient Federated Learning for Object Detection
Ka-Ho Chow, Ling Liu, Wenqi Wei +2
Federated Learning (FL) has been gaining popularity as a collaborative learning framework to train deep learning-based object detection models over a distributed population of clie…
Understanding Object Detection Through An Adversarial Lens
Ka-Ho Chow, Ling Liu, Mehmet Emre Gursoy +3
Deep neural networks based object detection models have revolutionized computer vision and fueled the development of a wide range of visual recognition applications. However, recen…