Correlated Anomaly Detection from Large Streaming Data

19 Dec 2018Zheng ChenXinli YuYuan LingBo SongWei QuanXiaohua HuErjia Yan

Correlated anomaly detection (CAD) from streaming data is a type of group anomaly detection and an essential task in useful real-time data mining applications like botnet detection, financial event detection, industrial process monitor, etc. The primary approach for this type of detection in previous researches is based on principal score (PS) of divided batches or sliding windows by computing top eigenvalues of the correlation matrix, e.g. the Lanczos algorithm... (read more)

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