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	Continuous, online anomaly region detection and tracking in networks
	Xie, Shuiyuan ; Ma, Xiuli ; Tang, Shiwei
	2013
英文摘要	In many real networks, the detection and tracking of unusual phenomena, such as the diffusion of contamination and the spreading of disease, is one of the key feature users are great interested in, which is called anomaly with technical terms. In this paper, we present a framework to detect and track anomaly region continuously. First, we build a state transition graph to summarize network's operating regularity, that is, network stays in a state for a period of time and alternates among states over and over again, which exists in many real networks. Second, we employ the state transition graph to predict network's next state. While comparing expected state and current state, we present suspicious region and its anomaly probability. We evaluate our approach on a real water distribution network from the Battle of the Water Sensor Network (BWSN). Experiments show that our approach is effective, efficient and scalable to detect and track anomaly region. ? 2013 Springer-Verlag.; EI; 0
语种	英语
DOI标识	10.1007/978-3-642-39527-7_9
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/294380]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Xie, Shuiyuan,Ma, Xiuli,Tang, Shiwei. Continuous, online anomaly region detection and tracking in networks. 2013-01-01.

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