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相关论文: OET: Optimization-based prompt injection Evaluatio…

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Previous insertion-based and paraphrase-based backdoors have achieved great success in attack efficacy, but they ignore the text quality and semantic consistency between poisoned and clean texts. Although recent studies introduce LLMs to…

计算与语言 · 计算机科学 2025-04-22 Zhengxian Wu , Juan Wen , Wanli Peng , Ziwei Zhang , Yinghan Zhou , Yiming Xue

Large Language Models (LLMs) are transforming cybersecurity by enabling intelligent, adaptive, and automated approaches to threat detection, vulnerability assessment, and incident response. With their advanced language understanding and…

密码学与安全 · 计算机科学 2025-07-21 Niveen O. Jaffal , Mohammed Alkhanafseh , David Mohaisen

As Large Language Models (LLMs) are increasingly integrated into academic peer review, their vulnerability to adversarial hidden prompts, i.e., adversarial instructions embedded in submissions to manipulate outcomes, poses a critical threat…

计算与语言 · 计算机科学 2026-05-29 Yuan Xin , Yixuan Weng , Minjun Zhu , Ying Ling , Chengwei Qin , Michael Backes , Yue Zhang , Linyi Yang

Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse applications, yet they pose significant security risks that threaten their safe deployment in critical domains. Current security alignment methodologies…

密码学与安全 · 计算机科学 2025-07-22 Pengfei Du

Prompt engineering significantly influences the reliability and clinical utility of Large Language Models (LLMs) in medical applications. Current optimization approaches inadequately address domain-specific medical knowledge and safety…

计算与语言 · 计算机科学 2025-08-26 Yinda Chen , Yangfan He , Jing Yang , Dapeng Zhang , Zhenlong Yuan , Muhammad Attique Khan , Jamel Baili , Por Lip Yee

Tool-augmented Large Language Model (LLM) agents have demonstrated impressive capabilities in automating complex, multi-step real-world tasks, yet remain vulnerable to indirect prompt injection. Adversaries exploit this weakness by…

密码学与安全 · 计算机科学 2026-05-12 Wei Zhao , Zhe Li , Peixin Zhang , Jun Sun

The rapid advancement and widespread adoption of generative artificial intelligence (GenAI) and large language models (LLMs) has been accompanied by the emergence of new security vulnerabilities and challenges, such as jailbreaking and…

Prompt injection attack, where an attacker injects a prompt into the original one, aiming to make an Large Language Model (LLM) follow the injected prompt to perform an attacker-chosen task, represent a critical security threat. Existing…

密码学与安全 · 计算机科学 2025-09-16 Zedian Shao , Hongbin Liu , Jaden Mu , Neil Zhenqiang Gong

Command injection vulnerabilities are a significant security threat in dynamic languages like Python, particularly in widely used open-source projects where security issues can have extensive impact. With the proven effectiveness of Large…

软件工程 · 计算机科学 2025-05-22 Yuxuan Wang , Jingshu Chen , Qingyang Wang

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

Modern large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities for coding tasks including writing and reasoning about code. They improve upon previous neural network models of code, such as code2seq or…

机器学习 · 计算机科学 2023-11-23 Chi Zhang , Zifan Wang , Ravi Mangal , Matt Fredrikson , Limin Jia , Corina Pasareanu

Large Language Models (LLMs) have demonstrated remarkable capabilities in natural language processing tasks, but their vulnerability to jailbreak attacks poses significant security risks. This survey paper presents a comprehensive analysis…

计算与语言 · 计算机科学 2024-12-18 Tarun Raheja , Nilay Pochhi , F. D. C. M. Curie

Log analysis is a relevant research field in cybersecurity as they can provide a source of information for the detection of threats to networks and systems. This paper presents a pipeline to use fine-tuned Large Language Models (LLMs) for…

密码学与安全 · 计算机科学 2025-07-04 Jorge J. Tejero-Fernández , Alfonso Sánchez-Macián

Large Language Models increasingly power critical infrastructure from healthcare to finance, yet their vulnerability to adversarial manipulation threatens system integrity and user safety. Despite growing deployment, no comprehensive…

密码学与安全 · 计算机科学 2026-03-19 Taiwo Onitiju , Iman Vakilinia

Large Language Models (LLMs) have demonstrated remarkable capabilities in code-related tasks, raising concerns about their potential for automated exploit generation (AEG). This paper presents the first systematic study on LLMs'…

密码学与安全 · 计算机科学 2025-05-05 David Jin , Qian Fu , Yuekang Li

Large language models have gained widespread prominence, yet their vulnerability to prompt injection and other adversarial attacks remains a critical concern. This paper argues for a security-by-design AI paradigm that proactively mitigates…

密码学与安全 · 计算机科学 2025-10-02 Dalal Alharthi , Ivan Roberto Kawaminami Garcia

The advent of large language models (LLMs) such as ChatGPT has attracted considerable attention in various domains due to their remarkable performance and versatility. As the use of these models continues to grow, the importance of…

神经与进化计算 · 计算机科学 2024-01-19 Jill Baumann , Oliver Kramer

Ensuring LLM alignment is critical to information security as AI models become increasingly widespread and integrated in society. Unfortunately, many defenses against adversarial attacks and jailbreaking on LLMs cannot adapt quickly to new…

密码学与安全 · 计算机科学 2025-08-12 Ivan Zhang

Large Language Models (LLMs) are increasingly becoming the preferred foundation platforms for many Natural Language Processing tasks such as Machine Translation, owing to their quality often comparable to or better than task-specific…

计算与语言 · 计算机科学 2024-03-18 Zhifan Sun , Antonio Valerio Miceli-Barone

The rapid integration of Multimodal Large Language Models (MLLMs) into critical applications is increasingly hindered by persistent safety vulnerabilities. However, existing red-teaming benchmarks are often fragmented, limited to…

密码学与安全 · 计算机科学 2026-01-13 Xin Wang , Yunhao Chen , Juncheng Li , Yixu Wang , Yang Yao , Tianle Gu , Jie Li , Yan Teng , Yingchun Wang , Xia Hu