标题： 大规模语言模型在网络安全中的应用、漏洞和防御技术 显示英文标题

标题： Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques

摘要： 大型语言模型（LLMs）正在通过实现智能、自适应和自动化的威胁检测、漏洞评估和事件响应方法，改变网络安全领域。 凭借其先进的语言理解和上下文推理能力，LLMs在处理物联网、区块链和硬件安全等领域的挑战方面超越了传统方法。 本综述提供了对LLMs在网络安全中应用的全面概述，重点集中在两个核心领域：（1）LLMs在关键网络安全领域的集成，以及（2）LLMs自身的漏洞及其缓解策略。 通过综合最近的进展并识别关键限制，这项工作为利用LLMs构建安全、可扩展且面向未来的网络防御系统提供了实用见解和战略建议。 显示英文摘要

摘要： 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 contextual reasoning, LLMs surpass traditional methods in tackling challenges across domains such as IoT, blockchain, and hardware security. This survey provides a comprehensive overview of LLM applications in cybersecurity, focusing on two core areas: (1) the integration of LLMs into key cybersecurity domains, and (2) the vulnerabilities of LLMs themselves, along with mitigation strategies. By synthesizing recent advancements and identifying key limitations, this work offers practical insights and strategic recommendations for leveraging LLMs to build secure, scalable, and future-ready cyber defense systems.