基于机器学习的网络攻击检测与防御技术研究初探
An Initial Study on Machine Learning-based Network Attack Detection and Defense Technology
徐东1
作者信息
- 1. 上海慕知文化传媒有限公司,上海 200030
- 折叠
摘要
本文探讨了基于机器学习的网络攻击检测和防御技术的研究现状和发展趋势,基于NSL-KDD数据集,采用不同的机器学习算法设计并实现了一个网络攻击检测和防御系统,并通过实验结果对所设计的系统进行了性能评估和分析.实验结果表明,所设计的系统具有较好的分类性能和防御效果,能够有效检测和防御各种网络攻击行为.
Abstract
This paper discusses the current research status and development trend of machine learning-based network attack detection and defense technologies,designs and implements a network attack detection and defense system based on the NSL-KDD dataset using different machine learning algorithms,and evaluates and analyzes the performance of the designed system through experimental results.The experimental results show that the designed system has better classification performance and defense effect,and can effectively detect and defend various network attacks.
关键词
机器学习/网络安全/网络攻击/NSL-KDD数据集/算法设计Key words
machine learning/cyber security/cyber attack/NSL-KDD dataset/algorithm design引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据