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Received:December 21, 2010 Revised:February 14, 2011
Received:December 21, 2010 Revised:February 14, 2011
中文摘要: 提出了使用日志的孤立点分析方法,对日志数据进行预处理,确立合适的挖掘粒度,刻画出正常模式.改进的方法可对规模较大的数据集进行异常检测时,在降低误报率的同时,大大提高了检测率,并达到理想的时间效率.使系统定期分析用户日志,从其自动找到可疑的日志,及时预防或者处理非法操作的现象,提高检测系统的智能化、准确性和检测效率.
Abstract:The use of log analysis of the outlier was proposed, on the log data preprocessing to establish the appropriate mining size, with depicting a normal mode. The improved method can be used for the large-scale anomalous detection of data sets, reducing the false alarm rate, while greatly improving the detection rate to achieve the desired time efficiency. The system can be with the regular analysis of the user logs, to automatically find the suspect from the log, in a timely manner to prevent or deal with the illegal operation, in order to make the detection system more intelligent, accurate and efficient.
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引用文本：
陈海宇,曾德胜.使用日志的异常检测.计算机系统应用,2011,20(9):90-94
CHEN Hai-Yu,ZENG De-Sheng.Anomaly Detection on the Use of Log.COMPUTER SYSTEMS APPLICATIONS,2011,20(9):90-94
陈海宇,曾德胜.使用日志的异常检测.计算机系统应用,2011,20(9):90-94
CHEN Hai-Yu,ZENG De-Sheng.Anomaly Detection on the Use of Log.COMPUTER SYSTEMS APPLICATIONS,2011,20(9):90-94
