摘要
由于网络安全数据量庞大和愈加复杂的网络入侵方式,传统的网络安全产品的攻击预测方法已变得不再适用。通过对网络流量日志的研究,提出了采用多模态可视化展示结构和快速异构树查询算法的实时网络流量日志可视化方法,开发并设计了大规模网络攻击预测可视分析系统Monic。结果表明,利用该系统通过交互分析能有效识别攻击者行为,预测网络攻击。
Traditional methods depends security products to prediction attack are no longer applied due to the large scale of network security data because the network intrusion mode become more and more Huge and complex. Through the studied of netflow data,a new method to real- time visual analysis netflow log with multi- modal display structure and heterogeneous tree netflow data organization structure was proposed and a visual analysis system of prediction attack for large- scale network named Monic is designed and researched. The ability of system to recognize attacker behavior and prediction network attack use this system through interaction analysis were indicated by results.
出处
《西南科技大学学报》
CAS
2015年第2期74-80,共7页
Journal of Southwest University of Science and Technology
基金
国家自然科学基金(61303127)
核废物与环境安全国防重点学科实验室(13zxnk12)
四川省教育厅重点项目(13ZA0169)
四川省科技创新苗子工程资助项目基金(2014-044)
关键词
可视分析
攻击预测
网络安全
多模态
大规模网络
Visual analysis
Attack prediction
Network security
Multi-modal
Large-scale network
