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相关论文: Intention Analysis Makes LLMs A Good Jailbreak Def…

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The jailbreak attack can bypass the safety measures of a Large Language Model (LLM), generating harmful content. This misuse of LLM has led to negative societal consequences. Currently, there are two main approaches to address jailbreak…

计算与语言 · 计算机科学 2024-03-25 Zezhong Wang , Fangkai Yang , Lu Wang , Pu Zhao , Hongru Wang , Liang Chen , Qingwei Lin , Kam-Fai Wong

As deep learning advances, Large Language Models (LLMs) and their multimodal counterparts, Multimodal Large Language Models (MLLMs), have shown exceptional performance in many real-world tasks. However, MLLMs face significant security…

密码学与安全 · 计算机科学 2024-10-23 Fenghua Weng , Yue Xu , Chengyan Fu , Wenjie Wang

Large language models (LLMs) are increasingly being adopted in a wide range of real-world applications. Despite their impressive performance, recent studies have shown that LLMs are vulnerable to deliberately crafted adversarial prompts…

人工智能 · 计算机科学 2024-06-17 Wei Zhao , Zhe Li , Yige Li , Ye Zhang , Jun Sun

The rapid development of Large Language Models (LLMs) has brought impressive advancements across various tasks. However, despite these achievements, LLMs still pose inherent safety risks, especially in the context of jailbreak attacks. Most…

密码学与安全 · 计算机科学 2025-06-19 Shi Lin , Hongming Yang , Rongchang Li , Xun Wang , Changting Lin , Wenpeng Xing , Meng Han

Recently, Large Reasoning Models (LRMs) have demonstrated superior logical capabilities compared to traditional Large Language Models (LLMs), gaining significant attention. Despite their impressive performance, the potential for stronger…

计算与语言 · 计算机科学 2025-05-27 Viet-Anh Nguyen , Shiqian Zhao , Gia Dao , Runyi Hu , Yi Xie , Luu Anh Tuan

Large language models (LLMs) have revolutionized artificial intelligence, but their increasing deployment across critical domains has raised concerns about their abnormal behaviors when faced with malicious attacks. Such vulnerability…

软件工程 · 计算机科学 2025-04-02 Shide Zhou , Tianlin Li , Kailong Wang , Yihao Huang , Ling Shi , Yang Liu , Haoyu Wang

Iterative jailbreak methods that repeatedly rewrite and input prompts into large language models (LLMs) to induce harmful outputs -- using the model's previous responses to guide each new iteration -- have been found to be a highly…

计算与语言 · 计算机科学 2025-10-21 Masahiro Kaneko , Zeerak Talat , Timothy Baldwin

Large Language Models (LLMs) are increasingly popular, powering a wide range of applications. Their widespread use has sparked concerns, especially through jailbreak attacks that bypass safety measures to produce harmful content. In this…

密码学与安全 · 计算机科学 2025-12-25 Zhengchun Shang , Wenlan Wei , Weiheng Bai

Adversarial misuse, particularly through `jailbreaking' that circumvents a model's safety and ethical protocols, poses a significant challenge for Large Language Models (LLMs). This paper delves into the mechanisms behind such successful…

计算与语言 · 计算机科学 2024-02-27 Huijie Lv , Xiao Wang , Yuansen Zhang , Caishuang Huang , Shihan Dou , Junjie Ye , Tao Gui , Qi Zhang , Xuanjing Huang

Large language models (LLMs) are vulnerable to jailbreak attacks - resulting in harmful, unethical, or biased text generations. However, existing jailbreaking methods are computationally costly. In this paper, we propose the weak-to-strong…

计算与语言 · 计算机科学 2025-07-25 Xuandong Zhao , Xianjun Yang , Tianyu Pang , Chao Du , Lei Li , Yu-Xiang Wang , William Yang Wang

Although Large Language Models (LLMs) have demonstrated significant capabilities in executing complex tasks in a zero-shot manner, they are susceptible to jailbreak attacks and can be manipulated to produce harmful outputs. Recently, a…

密码学与安全 · 计算机科学 2024-11-07 Zhao Xu , Fan Liu , Hao Liu

Large Language Models (LLMs) are trained with safety alignment to prevent generating malicious content. Although some attacks have highlighted vulnerabilities in these safety-aligned LLMs, they typically have limitations, such as…

机器学习 · 计算机科学 2026-03-11 Jesson Wang , Zhanhao Hu , David Wagner

Ensuring the safety and alignment of large language models (LLMs) with human values is crucial for generating responses that are beneficial to humanity. While LLMs have the capability to identify and avoid harmful queries, they remain…

计算与语言 · 计算机科学 2024-10-22 Yihua Zhou , Xiaochuan Shi

Recent advances in large language models (LLMs) have demonstrated remarkable potential in the field of natural language processing. Unfortunately, LLMs face significant security and ethical risks. Although techniques such as safety…

密码学与安全 · 计算机科学 2025-05-27 Qingsong Zou , Jingyu Xiao , Qing Li , Zhi Yan , Yuhang Wang , Li Xu , Wenxuan Wang , Kuofeng Gao , Ruoyu Li , Yong Jiang

Large Language Models (LLMs) have demonstrated remarkable capabilities across various tasks, yet they remain vulnerable to adversarial manipulations such as jailbreaking via prompt injection attacks. These attacks bypass safety mechanisms…

机器学习 · 计算机科学 2025-07-08 Xin Wei Chia , Swee Liang Wong , Jonathan Pan

Large Language Models (LLMs) are vulnerable to jailbreak attacks that exploit weaknesses in traditional safety alignment, which often relies on rigid refusal heuristics or representation engineering to block harmful outputs. While they are…

计算与语言 · 计算机科学 2025-10-01 Yuyou Zhang , Miao Li , William Han , Yihang Yao , Zhepeng Cen , Ding Zhao

Large Language Models (LLMs) excel in various domains but pose inherent privacy risks. Existing methods to evaluate privacy leakage in LLMs often use memorized prefixes or simple instructions to extract data, both of which well-alignment…

密码学与安全 · 计算机科学 2025-05-19 Yidan Wang , Yanan Cao , Yubing Ren , Fang Fang , Zheng Lin , Binxing Fang

With the rise of generative large language models (LLMs) like LLaMA and ChatGPT, these models have significantly transformed daily life and work by providing advanced insights. However, as jailbreak attacks continue to circumvent built-in…

密码学与安全 · 计算机科学 2025-01-22 Wuyuao Mai , Geng Hong , Pei Chen , Xudong Pan , Baojun Liu , Yuan Zhang , Haixin Duan , Min Yang

Extensive efforts have been made before the public release of Large language models (LLMs) to align their behaviors with human values. However, even meticulously aligned LLMs remain vulnerable to malicious manipulations such as…

密码学与安全 · 计算机科学 2024-10-01 Zeguan Xiao , Yan Yang , Guanhua Chen , Yun Chen

Most traditional AI safety research has approached AI models as machines and centered on algorithm-focused attacks developed by security experts. As large language models (LLMs) become increasingly common and competent, non-expert users can…

计算与语言 · 计算机科学 2024-01-25 Yi Zeng , Hongpeng Lin , Jingwen Zhang , Diyi Yang , Ruoxi Jia , Weiyan Shi