JOURNAL ARTICLE

Incremental Principal Component Analysis Method on Online Network Anomaly Detection

Abstract

Although PCA (principal component analysis) based multivariate anomaly detection algorithm can perform detection task, it cannot satisfy the needs of online detection due to the time complexity. To conquer this limitation, a multivariate online anomaly detection algorithm based on incremental PCA (IPCA) was proposed. The algorithm constructed normal model of traffic matrix incrementally and implemented online detection with this model. Analysis with Internet real traffic data and simulation data shows that this algorithm can perform online anomaly detection effectively.

Keywords:
Principal component analysis Anomaly detection Computer science Data mining Online algorithm Multivariate statistics Anomaly (physics) Artificial intelligence Pattern recognition (psychology) Algorithm Machine learning

Metrics

3
Cited By
0.47
FWCI (Field Weighted Citation Impact)
0
Refs
0.78
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Anomaly Detection Techniques and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Algorithms and Applications
Physical Sciences →  Engineering →  Control and Systems Engineering
Network Security and Intrusion Detection
Physical Sciences →  Computer Science →  Computer Networks and Communications
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