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Large Language Models (LLMs) are swiftly advancing in architecture and capability, and as they integrate more deeply into complex systems, the urgency to scrutinize their security properties grows. This paper surveys research in the…

计算与语言 · 计算机科学 2023-10-18 Erfan Shayegani , Md Abdullah Al Mamun , Yu Fu , Pedram Zaree , Yue Dong , Nael Abu-Ghazaleh

Large Language Models (LLMs) have become vital tools in software development tasks such as code generation, completion, and analysis. As their integration into workflows deepens, ensuring robustness against vulnerabilities especially those…

软件工程 · 计算机科学 2025-07-21 Yang Liu , Armstrong Foundjem , Foutse Khomh , Heng Li

Large Language Models (LLMs) are valuable for text classification, but their vulnerabilities must not be disregarded. They lack robustness against adversarial examples, so it is pertinent to understand the impacts of different types of…

计算与语言 · 计算机科学 2024-06-13 João Vitorino , Eva Maia , Isabel Praça

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

Large Language Models (LLMs) have achieved remarkable success but remain highly susceptible to jailbreak attacks, in which adversarial prompts coerce models into generating harmful, unethical, or policy-violating outputs. Such attacks pose…

The advancement of large language models has significantly improved natural language processing. However, challenges such as jailbreaks (prompt injections that cause an LLM to follow instructions contrary to its intended use),…

计算与语言 · 计算机科学 2024-05-24 Johan S Daniel , Anand Pal

The increasing deployment of Large Language Models (LLMs) in various applications necessitates a rigorous evaluation of their robustness against adversarial attacks. In this paper, we present a comprehensive study on the robustness of GPT…

计算与语言 · 计算机科学 2024-12-24 Yiyi Tao , Yixian Shen , Hang Zhang , Yanxin Shen , Lun Wang , Chuanqi Shi , Shaoshuai Du

Ensuring the security of large language models (LLMs) is an ongoing challenge despite their widespread popularity. Developers work to enhance LLMs security, but vulnerabilities persist, even in advanced versions like GPT-4. Attackers…

密码学与安全 · 计算机科学 2023-12-19 Aysan Esmradi , Daniel Wankit Yip , Chun Fai Chan

Large language models (LLMs) have significantly transformed the landscape of Natural Language Processing (NLP). Their impact extends across a diverse spectrum of tasks, revolutionizing how we approach language understanding and generations.…

密码学与安全 · 计算机科学 2025-06-13 Sara Abdali , Richard Anarfi , CJ Barberan , Jia He , Erfan Shayegani

The proliferation of large language models (LLMs) has sparked widespread and general interest due to their strong language generation capabilities, offering great potential for both industry and research. While previous research delved into…

人工智能 · 计算机科学 2024-07-09 Lukas Struppek , Minh Hieu Le , Dominik Hintersdorf , Kristian Kersting

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…

Over the past decade, there has been extensive research aimed at enhancing the robustness of neural networks, yet this problem remains vastly unsolved. Here, one major impediment has been the overestimation of the robustness of new defense…

人工智能 · 计算机科学 2023-10-31 Leo Schwinn , David Dobre , Stephan Günnemann , Gauthier Gidel

Large Language Model (LLM) watermarking embeds detectable signals into generated text for copyright protection, misuse prevention, and content detection. While prior studies evaluate robustness using watermark removal attacks, these methods…

密码学与安全 · 计算机科学 2025-09-16 Zhaoxi Zhang , Xiaomei Zhang , Yanjun Zhang , He Zhang , Shirui Pan , Bo Liu , Asif Qumer Gill , Leo Yu Zhang

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

As Large Language Models (LLMs) increasingly become key components in various AI applications, understanding their security vulnerabilities and the effectiveness of defense mechanisms is crucial. This survey examines the security challenges…

机器学习 · 计算机科学 2024-06-04 Frank Weizhen Liu , Chenhui Hu

The safety and robustness of large language models (LLMs) based applications remain critical challenges in artificial intelligence. Among the key threats to these applications are prompt hacking attacks, which can significantly undermine…

密码学与安全 · 计算机科学 2024-10-21 Baha Rababah , Shang , Wu , Matthew Kwiatkowski , Carson Leung , Cuneyt Gurcan Akcora

The integration of Large Language Models (LLMs) into healthcare applications offers promising advancements in medical diagnostics, treatment recommendations, and patient care. However, the susceptibility of LLMs to adversarial attacks poses…

人工智能 · 计算机科学 2024-12-18 Yifan Yang , Qiao Jin , Furong Huang , Zhiyong Lu

Large language models (LLMs) and LLM-based agents have been widely deployed in a wide range of applications in the real world, including healthcare diagnostics, financial analysis, customer support, robotics, and autonomous driving,…

密码学与安全 · 计算机科学 2025-05-20 Wenrui Xu , Keshab K. Parhi

Large language models (LLMs) have achieved record adoption in a short period of time across many different sectors including high importance areas such as education [4] and healthcare [23]. LLMs are open-ended models trained on diverse data…

密码学与安全 · 计算机科学 2024-12-24 Herve Debar , Sven Dietrich , Pavel Laskov , Emil C. Lupu , Eirini Ntoutsi

Large Language Models (LLMs) are deployed in interactive contexts with direct user engagement, such as chatbots and writing assistants. These deployments are vulnerable to prompt injection and jailbreaking (collectively, prompt hacking), in…

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