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Recent researches have shown that Large Language Models (LLMs) are susceptible to a security threat known as Backdoor Attack. The backdoored model will behave well in normal cases but exhibit malicious behaviours on inputs inserted with a…

密码学与安全 · 计算机科学 2024-04-04 Yunzhuo Hao , Wenkai Yang , Yankai Lin

Security concerns related to Large Language Models (LLMs) have been extensively explored, yet the safety implications for Multimodal Large Language Models (MLLMs), particularly in medical contexts (MedMLLMs), remain insufficiently studied.…

密码学与安全 · 计算机科学 2024-08-22 Xijie Huang , Xinyuan Wang , Hantao Zhang , Yinghao Zhu , Jiawen Xi , Jingkun An , Hao Wang , Hao Liang , Chengwei Pan

Large Language Models (LLMS) have increasingly become central to generating content with potential societal impacts. Notably, these models have demonstrated capabilities for generating content that could be deemed harmful. To mitigate these…

密码学与安全 · 计算机科学 2024-05-20 Zihao Xu , Yi Liu , Gelei Deng , Yuekang Li , Stjepan Picek

Large Language Models (LLMs) represent a transformative leap in artificial intelligence, enabling the comprehension, generation, and nuanced interaction with human language on an unparalleled scale. However, LLMs are increasingly vulnerable…

密码学与安全 · 计算机科学 2025-02-06 Nan Wang , Kane Walter , Yansong Gao , Alsharif Abuadbba

The advent of Large Language Models (LLMs) has marked significant achievements in language processing and reasoning capabilities. Despite their advancements, LLMs face vulnerabilities to data poisoning attacks, where the adversary inserts…

Warning: This article includes red-teaming experiments, which contain examples of compromised LLM responses that may be offensive or upsetting. Large Language Models (LLMs) have the potential to create harmful content, such as generating…

密码学与安全 · 计算机科学 2026-03-18 Ali Raza , Gurang Gupta , Nikolay Matyunin , Jibesh Patra

Large Language Models (LLMs) demonstrate impressive capabilities across various fields, yet their increasing use raises critical security concerns. This article reviews recent literature addressing key issues in LLM security, with a focus…

密码学与安全 · 计算机科学 2025-11-26 Benji Peng , Keyu Chen , Ming Li , Pohsun Feng , Ziqian Bi , Junyu Liu , Xinyuan Song , Qian Niu

Recent advancements in Large Language Models (LLMs) have sparked widespread concerns about their safety. Recent work demonstrates that safety alignment of LLMs can be easily removed by fine-tuning with a few adversarially chosen…

计算与语言 · 计算机科学 2025-03-03 Samuele Poppi , Zheng-Xin Yong , Yifei He , Bobbie Chern , Han Zhao , Aobo Yang , Jianfeng Chi

Large language models (LLMs) represent significant breakthroughs in artificial intelligence and hold potential for applications within smart grids. However, as demonstrated in previous literature, AI technologies are susceptible to various…

密码学与安全 · 计算机科学 2025-04-22 Jiangnan Li , Yingyuan Yang , Jinyuan Sun

This research article critically examines the potential risks and implications arising from the malicious utilization of large language models(LLM), focusing specifically on ChatGPT and Google's Bard. Although these large language models…

密码学与安全 · 计算机科学 2023-05-25 P. V. Sai Charan , Hrushikesh Chunduri , P. Mohan Anand , Sandeep K Shukla

The increasing demand for customized Large Language Models (LLMs) has led to the development of solutions like GPTs. These solutions facilitate tailored LLM creation via natural language prompts without coding. However, the trustworthiness…

密码学与安全 · 计算机科学 2024-05-29 Rui Zhang , Hongwei Li , Rui Wen , Wenbo Jiang , Yuan Zhang , Michael Backes , Yun Shen , Yang Zhang

Large Language Models (LLMs) are being enhanced with the ability to use tools and to process multiple modalities. These new capabilities bring new benefits and also new security risks. In this work, we show that an attacker can use visual…

As safety remains a crucial concern throughout the development lifecycle of Large Language Models (LLMs), researchers and industrial practitioners have increasingly focused on safeguarding and aligning LLM behaviors with human preferences…

计算与语言 · 计算机科学 2024-07-11 Jiayang Song , Yuheng Huang , Zhehua Zhou , Lei Ma

Large Language Models (LLMs) have become central to numerous natural language processing tasks, but their vulnerabilities present significant security and ethical challenges. This systematic survey explores the evolving landscape of attack…

密码学与安全 · 计算机科学 2025-05-05 Zhiyu Liao , Kang Chen , Yuanguo Lin , Kangkang Li , Yunxuan Liu , Hefeng Chen , Xingwang Huang , Yuanhui Yu

With the development of large language models (LLMs) like ChatGPT, both their vast applications and potential vulnerabilities have come to the forefront. While developers have integrated multiple safety mechanisms to mitigate their misuse,…

计算与语言 · 计算机科学 2024-07-23 Xiao Liu , Liangzhi Li , Tong Xiang , Fuying Ye , Lu Wei , Wangyue Li , Noa Garcia

Reinforcement learning has shown remarkable performance in aligning language models with human preferences, leading to the rise of attention towards developing RLHF platforms. These platforms enable users to fine-tune models without…

机器学习 · 计算机科学 2025-03-06 Erfan Entezami , Ali Naseh

Current large language models (LLM) provide a strong foundation for large-scale user-oriented natural language tasks. Many users can easily inject adversarial text or instructions through the user interface, thus causing LLM model security…

计算与语言 · 计算机科学 2024-11-14 Chong Zhang , Mingyu Jin , Dong Shu , Taowen Wang , Dongfang Liu , Xiaobo Jin

Large Language Models (LLMs) have become a cornerstone in the field of Natural Language Processing (NLP), offering transformative capabilities in understanding and generating human-like text. However, with their rising prominence, the…

Large Language Models (LLMs) have evolved into Multimodal Large Language Models (MLLMs), significantly enhancing their capabilities by integrating visual information and other types, thus aligning more closely with the nature of human…

密码学与安全 · 计算机科学 2025-06-03 Youze Wang , Wenbo Hu , Yinpeng Dong , Jing Liu , Hanwang Zhang , Richang Hong

Large Language Models (LLMs) have revolutionized natural language processing, but their robustness against adversarial attacks remains a critical concern. We presents a novel white-box style attack approach that exposes vulnerabilities in…

计算与语言 · 计算机科学 2024-09-16 Zeyu Yang , Zhao Meng , Xiaochen Zheng , Roger Wattenhofer