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Recent steganographic schemes, starting with Meteor (CCS'21), rely on leveraging large language models (LLMs) to resolve a historically-challenging task of disguising covert communication as ``innocent-looking'' natural-language…

密码学与安全 · 计算机科学 2025-04-15 Neil Perry , Sanket Gupte , Nishant Pitta , Lior Rotem

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

The proliferation of Large Language Models (LLMs) has introduced critical security challenges, where adversarial actors can manipulate input prompts to cause significant harm and circumvent safety alignments. These prompt-based attacks…

The widespread adoption of Large Language Models (LLMs) in critical applications has introduced severe reliability and security risks, as LLMs remain vulnerable to notorious threats such as hallucinations, jailbreak attacks, and backdoor…

密码学与安全 · 计算机科学 2026-04-07 Shide Zhou , Kailong Wang , Ling Shi , Haoyu Wang

Large language models (LLMs) have demonstrated superior performance compared to previous methods on various tasks, and often serve as the foundation models for many researches and services. However, the untrustworthy third-party LLMs may…

密码学与安全 · 计算机科学 2024-04-02 Hai Huang , Zhengyu Zhao , Michael Backes , Yun Shen , Yang Zhang

Advances in AI offer the prospect of manipulating beliefs and behaviors on a population-wide level. Large language models and autonomous agents now let influence campaigns reach unprecedented scale and precision. Generative tools can expand…

Large Language Models (LLMs) have emerged as powerful tools in various research domains. This article examines their potential through a literature review and firsthand experimentation. While LLMs offer benefits like cost-effectiveness and…

人机交互 · 计算机科学 2024-04-10 M. Namvarpour , A. Razi

Large language models (LLMs) have achieved a milestone that undenia-bly changed many held beliefs in artificial intelligence (AI). However, there remains many limitations of these LLMs when it comes to true language understanding,…

计算与语言 · 计算机科学 2023-07-28 Walid S. Saba

Large Language Models (LLMs) are becoming vital tools that help us solve and understand complex problems by acting as digital assistants. LLMs can generate convincing explanations, even when only given the inputs and outputs of these…

计算与语言 · 计算机科学 2024-10-14 Rohan Ajwani , Shashidhar Reddy Javaji , Frank Rudzicz , Zining Zhu

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 advent of Large Language Models (LLMs) has revolutionized various applications by providing advanced natural language processing capabilities. However, this innovation introduces new cybersecurity challenges. This paper explores the…

密码学与安全 · 计算机科学 2024-06-18 Stephen Burabari Tete

Large language models (LLMs) are increasingly being used in Metaverse environments to generate dynamic and realistic content and to control the behavior of non-player characters (NPCs). However, the cybersecurity concerns associated with…

密码学与安全 · 计算机科学 2023-12-25 Hongyin Zhu

Large Language Models (LLMs) represent an advanced evolution of earlier, simpler language models. They boast enhanced abilities to handle complex language patterns and generate coherent text, images, audios, and videos. Furthermore, they…

密码学与安全 · 计算机科学 2024-03-01 Jun Huang , Jiawei Zhang , Qi Wang , Weihong Han , Yanchun Zhang

The use of large language models (LLMs) for qualitative analysis is gaining attention in various fields, including software engineering, where qualitative methods are essential for understanding human and social factors. This study aimed to…

软件工程 · 计算机科学 2025-03-11 Matheus de Morais Leça , Lucas Valença , Reydne Santos , Ronnie de Souza Santos

Large Language Models (LLMs) are emerging as transformative tools for software vulnerability detection, addressing critical challenges in the security domain. Traditional methods, such as static and dynamic analysis, often falter due to…

密码学与安全 · 计算机科学 2025-02-19 Ze Sheng , Zhicheng Chen , Shuning Gu , Heqing Huang , Guofei Gu , Jeff Huang

Large Language Models (LLMs) are rapidly transitioning from conversational assistants to autonomous agents embedded in critical organizational functions, including Security Operations Centers (SOCs), financial systems, and infrastructure…

密码学与安全 · 计算机科学 2026-01-06 Giuseppe Canale , Kashyap Thimmaraju

Malware analysis is a complex process of examining and evaluating malicious software's functionality, origin, and potential impact. This arduous process typically involves dissecting the software to understand its components, infection…

密码学与安全 · 计算机科学 2025-01-10 Brandon J Walton , Mst Eshita Khatun , James M Ghawaly , Aisha Ali-Gombe

Synthetic data refers to artificial samples generated by models. While it has been validated to significantly enhance the performance of large language models (LLMs) during training and has been widely adopted in LLM development, potential…

密码学与安全 · 计算机科学 2025-10-27 Zi Liang , Qingqing Ye , Xuan Liu , Yanyun Wang , Jianliang Xu , Haibo Hu

Large Language Models (LLMs) and generative AI (GenAI) systems, such as ChatGPT, Claude, Gemini, LLaMA, and Copilot (by OpenAI, Anthropic, Google, Meta, and Microsoft, respectively), are reshaping digital platforms and app ecosystems while…

密码学与安全 · 计算机科学 2025-07-29 Kiarash Ahi

Large Language Models (LLMs) are increasingly being integrated into various applications. The functionalities of recent LLMs can be flexibly modulated via natural language prompts. This renders them susceptible to targeted adversarial…

密码学与安全 · 计算机科学 2023-05-08 Kai Greshake , Sahar Abdelnabi , Shailesh Mishra , Christoph Endres , Thorsten Holz , Mario Fritz