基于数据挖掘的异常检测模型

Anomaly Detection Model Based on Data Mining

提出了一种基于数据挖掘的异常检测模型 ,按此模型建成的系统具有可扩展性、自适应性和准确性等特点。另外 ,对模型的关键技术进行了详细的阐述 ,包括 :数据预处理技术、数据挖掘算法、规则库建立和维护技术、决策等。

In this paper, anomaly detection model based on data mining is proposed. The system with this model is extensible, accurate and adaptive. Moreover, this paper discusses some key technologies in this model, which include the data pre-processing technology, algorithms of data mining, rules library's establishment and update, decision-making and so on.