Ιδρυματικό Αποθετήριο [SANDBOX]
Πολυτεχνείο Κρήτης
EN  |  EL

Αναζήτηση

Πλοήγηση

Ο Χώρος μου

In-network PCA and anomaly detection

Huang Ling, Nguyen XuanLong, Garofalakis Minos, Jordan Michael I., Joseph Anthony, Taft Nina

Απλή Εγγραφή

URIhttp://purl.tuc.gr/dl/dias/ABF8CEBF-57C5-4563-B3FC-989DAAE7238B-
Αναγνωριστικόhttp://papers.nips.cc/paper/3156-in-network-pca-and-anomaly-detection.pdf-
Γλώσσαen-
Μέγεθος8 pagesen
ΤίτλοςIn-network PCA and anomaly detectionen
ΔημιουργόςHuang Lingen
ΔημιουργόςNguyen XuanLongen
ΔημιουργόςGarofalakis Minosen
ΔημιουργόςΓαροφαλακης Μινωςel
ΔημιουργόςJordan Michael I.en
ΔημιουργόςJoseph Anthonyen
ΔημιουργόςTaft Ninaen
ΠερίληψηWe consider the problem of network anomaly detection in large distributed systems. In this setting, Principal Component Analysis (PCA) has been proposed as a method for discovering anomalies by continuously tracking the projection of the data onto a residual subspace. This method was shown to work well empirically in highly aggregated networks, that is, those with a limited number of large nodes and at coarse time scales. This approach, however, has scalability limitations. To overcome these limitations, we develop a PCA-based anomaly detector in which adaptive local data filters send to a coordinator just enough data to enable accurate global detection. Our method is based on a stochastic matrix perturbation analysis that characterizes the tradeoff between the accuracy of anomaly detection and the amount of data communicated over the network.en
ΤύποςΠλήρης Δημοσίευση σε Συνέδριοel
ΤύποςConference Full Paperen
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-12-01-
Ημερομηνία Δημοσίευσης2006-
Θεματική ΚατηγορίαDatabases en
Θεματική ΚατηγορίαManagementen
Βιβλιογραφική ΑναφοράL. Huang, X. Nguyen, M. Garofalakis, M. I. Jordan, A. Joseph and N. Taft, "In-network PCA and anomaly detection", in 20th Annual Conference on Neural Information Processing Systems, 2006. en

Υπηρεσίες

Στατιστικά

 

Copyright © DIAS 2013