7 citations · 15 across the 18 of their papers we have counts for
10 papers · 1 filter
GradSentry: Gradient Spectral Entropy for Backdoor Sample Filtering in Large Language Model Fine-Tuning
Haodong Zhao, Tianyi Xu, Tianhang Zhao +2
Fine-tuning Large Language Models with untrusted data exposes models to backdoor attacks, where poisoned samples cause targeted misbehavior. Existing sample-filtering defenses rely…
EmbTracker: Traceable Black-box Watermarking for Federated Language Models
Haodong Zhao, Jinming Hu, Yijie Bai +6
Federated Language Model (FedLM) allows a collaborative learning without sharing raw data, yet it introduces a critical vulnerability, as every untrustworthy client may leak the re…
ProtegoFed: Backdoor-Free Federated Instruction Tuning with Interspersed Poisoned Data
Haodong Zhao, Jinming Hu, Zhaomin Wu +7
Federated Instruction Tuning (FIT) enables collaborative instruction tuning of large language models across multiple organizations (clients) in a cross-silo setting without requiri…
Revisiting Backdoor Threat in Federated Instruction Tuning from a Signal Aggregation Perspective
Haodong Zhao, Jinming Hu, Gongshen Liu
Federated learning security research has predominantly focused on backdoor threats from a minority of malicious clients that intentionally corrupt model updates. This paper challen…
Patronus: Identifying and Mitigating Transferable Backdoors in Pre-trained Language Models
Tianhang Zhao, Haodong Zhao, Wei Du +5
The ``Pre-train, then fine-tune'' paradigm has revolutionized Natural Language Processing (NLP). In this context, transferable backdoors pose a severe threat to the Pre-trained Lan…
GhostEI-Bench: Do Mobile Agents Resilience to Environmental Injection in Dynamic On-Device Environments?
Chiyu Chen, Xinhao Song, Yunkai Chai +7
Vision-Language Models (VLMs) are increasingly deployed as autonomous agents to navigate mobile graphical user interfaces (GUIs). Operating in dynamic on-device ecosystems, which i…
NSmark: Null Space Based Black-box Watermarking Defense Framework for Language Models
Haodong Zhao, Jinming Hu, Peixuan Li +6
Language models (LMs) have emerged as critical intellectual property (IP) assets that necessitate protection. Although various watermarking strategies have been proposed, they rema…
Revisiting the Information Capacity of Neural Network Watermarks: Upper Bound Estimation and Beyond
Fangqi Li, Haodong Zhao, Wei Du +1
To trace the copyright of deep neural networks, an owner can embed its identity information into its model as a watermark. The capacity of the watermark quantify the maximal volume…
Backdoor Attacks and Countermeasures in Natural Language Processing Models: A Comprehensive Security Review
Pengzhou Cheng, Zongru Wu, Wei Du +3
Language Models (LMs) are becoming increasingly popular in real-world applications. Outsourcing model training and data hosting to third-party platforms has become a standard metho…
A Universal Identity Backdoor Attack against Speaker Verification based on Siamese Network
Haodong Zhao, Wei Du, Junjie Guo +1
Speaker verification has been widely used in many authentication scenarios. However, training models for speaker verification requires large amounts of data and computing power, so…