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题名:
incremental outlier detection in data streams using local correlation integral
作者: Lu Xinjie ; Yang Tian ; Liao Zaifei ; Elahi Manzoor ; Liu Wei ; Wang Hongan
会议文集: Proceedings of the ACM Symposium on Applied Computing
会议名称: 24th Annual ACM Symposium on Applied Computing, SAC 2009
会议日期: 37323
出版日期: 2009
会议地点: Honolulu, HI, United states
关键词: Computer science ; Data communication systems
出版地: United States
ISBN: 9781605581668
部门归属: (1) Graduate University, Chinese Academy of Sciences, Beijing, China; (2) Institute of Software, Chinese Academy of Sciences, Beijing, China; (3) State Key Lab. of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China
主办者: ACM SIGAPP
英文摘要: In this paper, an incremental outlier detection technique capable of dealing with a large amount of data is presented and evaluated in the context of intrusion detection. The proposed method is based on the LOcal Correlation Integral (LOCI for short). The detection technique consists of two parts. The first part named insertion receives the sequence of input point and updates Multi-granularity DEviation Factor (MDEF) of the point at intervals. The second part named deletion deletes one or a batch of points. This technique is able to process streaming data in a single scan. Moreover, the number of updates in the incremental LOCI algorithm per insertion/deletion of a single data record does not depend on the total number of data records. Experimental results with real life data sets show that the technique is capable of dealing with data streams, successfully detecting outlier. Copyright 2009 ACM.
内容类型: 会议论文
URI标识: http://ir.iscas.ac.cn/handle/311060/8492
Appears in Collections:人机交互技术与智能信息处理实验室_会议论文

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Recommended Citation:
Lu Xinjie,Yang Tian,Liao Zaifei,et al. incremental outlier detection in data streams using local correlation integral[C]. 见:24th Annual ACM Symposium on Applied Computing, SAC 2009. Honolulu, HI, United states. 37323.
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