Supervised Anomaly Detection in Uncertain Pseudoperiodic Data Streams

• Published in: ACM transactions on Internet technology Vol. 16; no. 1; pp. 1 - 20
• Main Authors: Ma, Jiangang, Sun, Le, Wang, Hua, Zhang, Yanchun, Aickelin, Uwe
• Format: Journal Article
• Language: English
• Published: 01.01.2016
• Subjects: Anomalies; Applications programs; Classification; Computational efficiency; Data transmission; Feature extraction; Internet; Pattern recognition

Uncertain data streams have been widely generated in many Web applications. The uncertainty in data streams makes anomaly detection from sensor data streams far more challenging. In this article, we present a novel framework that supports anomaly detection in uncertain data streams. The proposed fra...