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针对传统异常检测系统的有效性、适应性和扩展性方面还存在不足,在传统的异常检测系统基础上,融合滥用检测、异常检测和数据挖掘技术,提出一种基于数据挖掘的移动对象异常检测ADMO模型,该系统模型的体系结构定位为分布式体系结构,系统分为检测前端和检测后端。实验证明基于该模型的检测系统可更有效地检测移动对象的异常。
Aiming at the effectiveness, adaptability and expansibility of the traditional anomaly detection system, there are still some shortcomings. Based on the traditional anomaly detection system, this paper proposes a data mining-based anomaly detection method based on data mining, combining with abuse detection, anomaly detection and data mining technology ADMO model, the system model of the architecture as a distributed architecture, the system is divided into detection front-end and detection back-end. Experiments show that the detection system based on this model can detect the moving object more effectively.