基于准实时流量数据报出与信息熵技术的网络流量异常监测研究

Research on Network Traffic Anomaly Detection Based on Quasi Real Time Traffic Data Reporting and Information Entropy Technology

网络流量异常监测主要通过数据仓库、OLAP、数据挖掘、WEB、ETL等相关技术,来提高网络监测数据处理和存储的效率,同时还可以通过信息熵技术保证精确性、简洁性,能够确保精确性的前提下更为简洁高效.针对这些技术,文中通过合理的架构,使得信息熵技术在功能性方面达到了决策更加有效合理的效果,同时还验证了信息熵技术框架的灵活性和可复用性.

Network traffic anomaly monitoring mainly through data warehouse, OLAP, data mining, WEB, ETL and other related technologies to improve the efficiency of network monitoring data processing and storage.At the same time, it can also ensure accuracy and simplicity through information entropy technology.It is more concise and efficient to ensure accuracy. According to these technologies, the information entropy technology has achieved more effective and reasonable results in terms of function, and the flexibility and reusability of the information entropy technology framework have also been verified.