13 citations · 21 across the 9 of their papers we have counts for
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cs.CR2024★ 3 cited
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…
cs.CR2024
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…
cs.CR2024★ 4 cited
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…