| 引用本文： |
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韦东泽,周天阳,朱俊虎,李治,朱浩杰.智能化渗透测试技术现状与未来发展综述[J].信息安全学报,已采用 [点击复制]
- WeiDongZe,Zhou Tianyang,Zhu Junhu,Li Zhi,Zhu Haojie.A Review of the Current Status and Future Develop-ment of Intelligent Penetration Testing Technology[J].Journal of Cyber Security,Accept [点击复制]
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| 摘要: |
| 在网络信息技术飞速发展的今天，政府部门和企业对网络的依赖日益增加，网络安全漏洞的威胁也随之增大。近年来，网络攻击事件频发，导致政府和企业财产受到重大损失。渗透测试可以帮助企业或组织发现并修复系统中的安全漏洞，降低遭受攻击的风险，但是传统的渗透测试依赖于训练有素的人类专家，成本高昂且效率低下，因此开发智能化渗透测试系统成为当务之急。本文全面综述了智能化渗透测试技术的研究进展、应用现状及未来发展趋势，旨在为网络安全领域的研究者和实践者提供深入洞见。文章首先界定了渗透测试的基本概念，并强调了其在网络安全防护中的核心作用。随后，深入探讨了智能化渗透测试的技术分类，特别是基于静态分析和强化学习的路径规划方法。通过系统总结现有研究在攻击路径规划中的技术原理和发展状况，对不同智能化渗透测试方法的应用效果进行了全面评估。文章进一步剖析了智能化渗透测试在实际应用中遇到的挑战和局限性，并对比分析了各种技术在提升渗透测试效率和准确性方面的优势。最后，对智能化渗透测试的未来发展方向进行了展望，特别是在大规模网络场景下的应用潜力、真实复杂网络环境下的攻击路径规划技术，以及结合大语言模型的新型渗透测试工具等方面提出了前瞻性的研究方向。本文的研究成果不仅为智能化渗透测试技术的进一步研究提供了参考和指导，也为网络安全实践提供了宝贵的技术支持和策略建议。 |
| 关键词: 智能化渗透测试 路径规划 静态分析 强化学习 |
| DOI： |
| 投稿时间：2024-10-31修订日期：2025-03-17 |
| 基金项目:河南省自然科学基金项目 |
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| A Review of the Current Status and Future Develop-ment of Intelligent Penetration Testing Technology |
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WeiDongZe, Zhou Tianyang, Zhu Junhu, Li Zhi, Zhu Haojie
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| (Information Engineering University) |
| Abstract: |
| In today's rapidly developing era of network information technology, government departments and enterprises are in-creasingly dependent on networks, and the threat of network security vulnerabilities is also growing. In recent years, frequent network attacks have caused significant losses to government and corporate assets. Penetration testing can help businesses and organizations discover and fix security vulnerabilities in their systems, reducing the risk of attacks. However, traditional penetration testing relies on highly trained human experts, which is costly and inefficient. There-fore, the development of intelligent penetration testing systems has become an urgent priority. This paper provides a comprehensive review of the research progress, current status, and future development trends of intelligent penetration testing technology, aiming to offer in-depth insights for researchers and practitioners in the field of cybersecurity. The article first defines the basic concept of penetration testing and emphasizes its core role in network security protection. It then delves into the technological classification of intelligent penetration testing, particularly the path planning methods based on static analysis and reinforcement learning. By systematically summarizing the technical principles and devel-opment status of existing research in attack path planning, the paper provides a comprehensive assessment of the appli-cation effects of various intelligent penetration testing methods. The article further analyzes the challenges and limita-tions encountered by intelligent penetration testing in practical applications and compares the advantages of various technologies in improving the efficiency and accuracy of penetration testing. Finally, the paper looks forward to the fu-ture development directions of intelligent penetration testing, especially its application potential in large-scale network scenarios, attack path planning technologies in real complex network environments, and the prospects of combining large language models with new types of penetration testing tools, proposing forward-looking research directions. The research findings of this paper not only provide references and guidance for further research in intelligent penetration testing technology but also offer valuable technical support and strategic suggestions for cybersecurity practice. |
| Key words: Intelligent Penetration Testing Path Planning Static Analysis Reinforcement Learning |
