@inproceedings{7089e603342740f4b5a70b75c2061d0e,
title = "Detecting and identifying network anomalies by component analysis",
abstract = "Many research works address detection and identification of network anomalies using traffic analysis. This paper considers large topologies, such as those of an ISP, with traffic analysis performed on multiple links simultaneously. This is made possible by using a combination of simple online traffic parameters and specific data from headers of selective packets. Even though large networks may have many network links and a lot of traffic, the analysis is simplified with the usage of Principal Component Analysis (PCA) subspace method. The proposed method proves that aggregation of such traffic profiles on large topologies allows identification of a certain set of anomalies with high level of certainty.",
keywords = "Anomaly detection, Anomaly identification, Network anomalies, Principal component analysis, Traffic analysis",
author = "Quyen, {Le The} and Marat Zhanikeev and Yoshiaki Tanaka",
year = "2006",
doi = "10.1007/11876601_51",
language = "English",
isbn = "3540457763",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "501--504",
booktitle = "Management of Convergence Networks and Services - 9th Asia-Pacific Network Operations and Management Symposium, APNOMS 2006, Proceedings",
note = "9th Asia-Pacific Network Operations and Management Symposium, APNOMS 2006 ; Conference date: 27-09-2006 Through 29-09-2006",
}