6 citations · 12 across the 6 of their papers we have counts for
6 papers
PRJ: Perception-Retrieval-Judgement for Generated Images
Qiang Fu, Zonglei Jing, Zonghao Ying +1
The rapid progress of generative AI has enabled remarkable creative capabilities, yet it also raises urgent concerns regarding the safety of AI-generated visual content in real-wor…
CS-Eval: A Comprehensive Large Language Model Benchmark for CyberSecurity
Zhengmin Yu, Jiutian Zeng, Siyi Chen +7
Over the past year, there has been a notable rise in the use of large language models (LLMs) for academic research and industrial practices within the cybersecurity field. However,…
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…
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…
DLP: towards active defense against backdoor attacks with decoupled learning process
Zonghao Ying, Bin Wu
Deep learning models are well known to be susceptible to backdoor attack, where the attacker only needs to provide a tampered dataset on which the triggers are injected. Models tra…
NBA: defensive distillation for backdoor removal via neural behavior alignment
Zonghao Ying, Bin Wu
Recently, deep neural networks have been shown to be vulnerable to backdoor attacks. A backdoor is inserted into neural networks via this attack paradigm, thus compromising the int…