| 摘 要: 在网络的攻防博弈中，传统网络空间的安全防御机制在海量网络动态隐藏信息中逐渐落于防守端下风，以目前网络空间安全存在的问题为出发点，首次从攻击与防御、知识与模型、漏洞与利用等角度进行人工智能与网络空间安全融合分析，以此为基础总结了基于人工智能的网络空间安全攻击分类。通过分析决策树、k邻近等深度学习算法的工作机制和适用场景，探讨了在垃圾邮件、恶意软件、网络异常等网络空间安全防御的应用，为网络空间安全在生成对抗网络为热点的环境下，构建有效的智能网络安全动态防御规则，为实现网络安全运维智能化、自动化提供参考。 |
| 关键词: 人工智能；网络空间安全；生成对抗网络；安全防御机制 |
|
中图分类号: TP393.2
文献标识码: A
|
| 基金项目: 2022年广东开放大学(广东理工职业学院)双师工作室项目“网络系统集成双师工作室”(12342127). |
|
| Research on Cyberspace Security Defense Rules based on Artificial Intelligence |
|
LIU Banggui
|
(School of Artificial Intelligence, the Open University of Guangdong, Guangzhou 510091, China )
liubanggui@qq.com
|
| Abstract: In the game of network attack and defense, traditional cyberspace security defense mechanism has gradually fallen behind the defense end in the massive network dynamic hidden information. Aiming at the problems of cyberspace security, this paper proposes to carry out fusion analysis of AI (Artificial Intelligence) and cyberspace security for the first time from the angles of attack and defense, knowledge and model, and vulnerability and utilization. On this basis, the classification of cyberspace security attacks based on AI is summarized. By analyzing the working mechanism and application scenarios of deep learning algorithms such as Decision Tree and K-Nearest Neighbor, this paper discusses the application of cyberspace security defense in spam, malware, network anomaly and so on. It provides a reference for cyberspace security to build effective intelligent dynamic defense rules for network security, and realize the intelligence and automation of network security operation and maintenance under the environment of Generative Adversarial Networks as a hot spot. |
| Keywords: artificial intelligence; cyberspace security; generative adversarial network; security defense mechanism |
