基于机器学习的DDoS攻击检测与防御策略研究
摘 要
本论文针对DDoS攻击检测和防御的问题，提出了基于机器学习和分布式防御的优化策略。在研究现状和未来目标的基础上，分析了现存问题包括误报和漏报率高、计算复杂度高、针对新型攻击方法的检测能力不足等，进而设计并实现了机器学习算法的DDoS攻击检测系统，通过优化算法和参数，提升了检测准确率和效率。同时，提出了基于分布式防御的系统解决方案，使安全防御能力更加强大。该研究对于提高信息网络的安全性、保障网络系统的可靠性和稳定性具有重要的现实意义。
关键词：DDoS攻击；机器学习；分布式防御
Abstract
Aiming at the problem of DDoS attack detection and defense, this paper proposes an optimization strategy based on machine learning and distributed defense. On the basis of the research status and future goals, the existing problems including high false positives and false negatives, high computational complexity, and insufficient detection ability against new attack methods are analyzed, and then the machine learning algorithm of DDoS attack detection system is designed and implemented. By optimizing the algorithm and parameters, the detection accuracy and efficiency are improved. At the same time, the system solution based on distributed defense is proposed to make the security defense more powerful. This research has important practical significance for improving the security of information network and ensuring the reliability and stability of network system.
Key words: DDoS attacks; machine learning; distributed defense
目 录
中文摘要 I
英文摘要 II
目 录 III
引 言 1
第1章、相关概念及理论基础 2
1.1、DDoS攻击的概念及分类 2
1.2、机器学习算法原理 2
1.3、DDoS攻击检测和防御的相关技术 3
第2章、DDoS攻击检测和防御存在的问题 4
2.1、误报和漏报率较高 4
2.2、处理大规模数据时计算复杂度很高 4
2.3、针对新型DDoS攻击方法的检测能力亟待提升 5
第3章、DDoS攻击检测和防御优化策略 6
3.1、设计并实现基于机器学习的DDoS攻击检测系统 6
3.2、优化机器学习模型算法及其相关参数 6
3.3、建立基于分布式防御的DDoS攻击防御系统 7
结 论 8
参考文献 9
摘 要
本论文针对DDoS攻击检测和防御的问题，提出了基于机器学习和分布式防御的优化策略。在研究现状和未来目标的基础上，分析了现存问题包括误报和漏报率高、计算复杂度高、针对新型攻击方法的检测能力不足等，进而设计并实现了机器学习算法的DDoS攻击检测系统，通过优化算法和参数，提升了检测准确率和效率。同时，提出了基于分布式防御的系统解决方案，使安全防御能力更加强大。该研究对于提高信息网络的安全性、保障网络系统的可靠性和稳定性具有重要的现实意义。
关键词：DDoS攻击；机器学习；分布式防御
Abstract
Aiming at the problem of DDoS attack detection and defense, this paper proposes an optimization strategy based on machine learning and distributed defense. On the basis of the research status and future goals, the existing problems including high false positives and false negatives, high computational complexity, and insufficient detection ability against new attack methods are analyzed, and then the machine learning algorithm of DDoS attack detection system is designed and implemented. By optimizing the algorithm and parameters, the detection accuracy and efficiency are improved. At the same time, the system solution based on distributed defense is proposed to make the security defense more powerful. This research has important practical significance for improving the security of information network and ensuring the reliability and stability of network system.
Key words: DDoS attacks; machine learning; distributed defense
目 录
中文摘要 I
英文摘要 II
目 录 III
引 言 1
第1章、相关概念及理论基础 2
1.1、DDoS攻击的概念及分类 2
1.2、机器学习算法原理 2
1.3、DDoS攻击检测和防御的相关技术 3
第2章、DDoS攻击检测和防御存在的问题 4
2.1、误报和漏报率较高 4
2.2、处理大规模数据时计算复杂度很高 4
2.3、针对新型DDoS攻击方法的检测能力亟待提升 5
第3章、DDoS攻击检测和防御优化策略 6
3.1、设计并实现基于机器学习的DDoS攻击检测系统 6
3.2、优化机器学习模型算法及其相关参数 6
3.3、建立基于分布式防御的DDoS攻击防御系统 7
结 论 8
参考文献 9
