4 citations · 17 across the 34 of their papers we have counts for
12 papers · 1 filter
TrapFlow: Controllable Website Fingerprinting Defense via Dynamic Backdoor Learning
Siyuan Liang, Jiajun Gong, Tianmeng Fang +5
Website fingerprinting (WF) attacks, which covertly monitor user communications to identify the web pages they visit, pose a serious threat to user privacy. Existing WF defenses at…
CopyrightShield: Enhancing Diffusion Model Security against Copyright Infringement Attacks
Zhixiang Guo, Siyuan Liang, Aishan Liu +1
Diffusion models have attracted significant attention due to its exceptional data generation capabilities in fields such as image synthesis. However, recent studies have shown that…
BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks
Yisong Xiao, Aishan Liu, Xinwei Zhang +6
Pre-trained large deep learning models are now serving as the dominant component for downstream middleware users and have revolutionized the learning paradigm, replacing the tradit…
SafeBench: A Safety Evaluation Framework for Multimodal Large Language Models
Zonghao Ying, Aishan Liu, Siyuan Liang +5
Multimodal Large Language Models (MLLMs) are showing strong safety concerns (e.g., generating harmful outputs for users), which motivates the development of safety evaluation bench…
Compromising Embodied Agents with Contextual Backdoor Attacks
Aishan Liu, Yuguang Zhou, Xianglong Liu +9
Large language models (LLMs) have transformed the development of embodied intelligence. By providing a few contextual demonstrations, developers can utilize the extensive internal…
LanEvil: Benchmarking the Robustness of Lane Detection to Environmental Illusions
Tianyuan Zhang, Lu Wang, Hainan Li +5
Lane detection (LD) is an essential component of autonomous driving systems, providing fundamental functionalities like adaptive cruise control and automated lane centering. Existi…
Unveiling the Safety of GPT-4o: An Empirical Study using Jailbreak Attacks
Zonghao Ying, Aishan Liu, Xianglong Liu +1
The recent release of GPT-4o has garnered widespread attention due to its powerful general capabilities. While its impressive performance is widely acknowledged, its safety aspects…
Temporal Feature Matters: A Framework for Diffusion Model Quantization
Yushi Huang, Ruihao Gong, Xianglong Liu +4
The Diffusion models, widely used for image generation, face significant challenges related to their broad applicability due to prolonged inference times and high memory demands. E…
Jailbreak Vision Language Models via Bi-Modal Adversarial Prompt
Zonghao Ying, Aishan Liu, Tianyuan Zhang +4
In the realm of large vision language models (LVLMs), jailbreak attacks serve as a red-teaming approach to bypass guardrails and uncover safety implications. Existing jailbreaks pr…
GenderBias-\emph{VL}: Benchmarking Gender Bias in Vision Language Models via Counterfactual Probing
Yisong Xiao, Aishan Liu, QianJia Cheng +6
Large Vision-Language Models (LVLMs) have been widely adopted in various applications; however, they exhibit significant gender biases. Existing benchmarks primarily evaluate gende…
LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit
Ruihao Gong, Yang Yong, Shiqiao Gu +5
Recent advancements in large language models (LLMs) are propelling us toward artificial general intelligence with their remarkable emergent abilities and reasoning capabilities. Ho…
Object Detectors in the Open Environment: Challenges, Solutions, and Outlook
Siyuan Liang, Wei Wang, Ruoyu Chen +5
With the emergence of foundation models, deep learning-based object detectors have shown practical usability in closed set scenarios. However, for real-world tasks, object detector…