Presentation 2002/9/24
Network Anomaly Detection using Statistical Clustering Method
Tatsuya OIKAWA, Yuji WAIZUMI, Kohei OHTA, Nei KATO, Yoshiaki NEMOTO,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) In network management, it is important to be able to detect anomalous events such as illegal entries and hardware breakdowns. Much attention in the past has been given to research providing this detection capability, such as IDS. This previous research is based upon misuse detction methods, however, such methods become ineffective against unprofiled ways of illegal entry. In addition, host-based methods of network management provide a smaller protection coverage, furthermore, network-based methods offer the same result as well. In this paper, we apply the anomaly detection method onto network conditions. A model of the network condition is created and this method is applied onto that framework in order to determine whether that network condition is either anomalous or normal. To prove the validity of the method, this method is then applied to the trace data of actual network traffic.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Anomaly Detection / Clustering / Dendrogram / Principal Component Analysis (PCA)
Paper # IN2002-87
Date of Issue

Conference Information
Committee IN
Conference Date 2002/9/24(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To Information Networks (IN)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Network Anomaly Detection using Statistical Clustering Method
Sub Title (in English)
Keyword(1) Anomaly Detection
Keyword(2) Clustering
Keyword(3) Dendrogram
Keyword(4) Principal Component Analysis (PCA)
1st Author's Name Tatsuya OIKAWA
1st Author's Affiliation Graduate School of Information Sciences, TOHOKU University()
2nd Author's Name Yuji WAIZUMI
2nd Author's Affiliation Graduate School of Information Sciences, TOHOKU University
3rd Author's Name Kohei OHTA
3rd Author's Affiliation Cyber Solutions. Inc.
4th Author's Name Nei KATO
4th Author's Affiliation Graduate School of Information Sciences, TOHOKU University
5th Author's Name Yoshiaki NEMOTO
5th Author's Affiliation Graduate School of Information Sciences, TOHOKU University
Date 2002/9/24
Paper # IN2002-87
Volume (vol) vol.102
Number (no) 351
Page pp.pp.-
#Pages 6
Date of Issue