3 papers
cs.CR2025
Enhancing Adversarial Transferability with Adversarial Weight Tuning
Jiahao Chen, Zhou Feng, Rui Zeng +6
Deep neural networks (DNNs) are vulnerable to adversarial examples (AEs) that mislead the model while appearing benign to human observers. A critical concern is the transferability…
cs.CR2025
NeuroBreak: Unveil Internal Jailbreak Mechanisms in Large Language Models
Chuhan Zhang, Ye Zhang, Bowen Shi +5
In deployment and application, large language models (LLMs) typically undergo safety alignment to prevent illegal and unethical outputs. However, the continuous advancement of jail…
cs.AI2024
Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents
Yuyou Gan, Yong Yang, Zhe Ma +10
With the continuous development of large language models (LLMs), transformer-based models have made groundbreaking advances in numerous natural language processing (NLP) tasks, lea…