13 citations · 21 across the 9 of their papers we have counts for
6 papers · 1 filter
Neutralizing Backdoors through Information Conflicts for Large Language Models
Chen Chen, Yuchen Sun, Xueluan Gong +2
Large language models (LLMs) have seen significant advancements, achieving superior performance in various Natural Language Processing (NLP) tasks, from understanding to reasoning.…
Hidden Data Privacy Breaches in Federated Learning
Xueluan Gong, Yuji Wang, Shuaike Li +5
Federated Learning (FL) emerged as a paradigm for conducting machine learning across broad and decentralized datasets, promising enhanced privacy by obviating the need for direct d…
PAPILLON: Efficient and Stealthy Fuzz Testing-Powered Jailbreaks for LLMs
Xueluan Gong, Mingzhe Li, Yilin Zhang +5
Large Language Models (LLMs) have excelled in various tasks but are still vulnerable to jailbreaking attacks, where attackers create jailbreak prompts to mislead the model to produ…
AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions
Chen Chen, Xueluan Gong, Ziyao Liu +3
AI Safety is an emerging area of critical importance to the safe adoption and deployment of AI systems. With the rapid proliferation of AI and especially with the recent advancemen…
Proactive Detection of Physical Inter-rule Vulnerabilities in IoT Services Using a Deep Learning Approach
Bing Huang, Chen Chen, Kwok-Yan Lam +1
Emerging Internet of Things (IoT) platforms provide sophisticated capabilities to automate IoT services by enabling occupants to create trigger-action rules. Multiple trigger-actio…
Threats, Attacks, and Defenses in Machine Unlearning: A Survey
Ziyao Liu, Huanyi Ye, Chen Chen +2
Machine Unlearning (MU) has recently gained considerable attention due to its potential to achieve Safe AI by removing the influence of specific data from trained Machine Learning…