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| Presentation | 2013-11-15 13:30 A Robust Principal Component Analysis for Traffic Anomaly Detection Takahiro Matsuda, Tatsuya Morita, Takanori Kudo, Tetsuya Takine (Osaka Univ.)  NS2013-128 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this article, we consider anomaly detection schemes for traffic traces measured in multiple links of a network. Principal Component Analysis (PCA) is a promising technique to detect anomalies in network traffic, and it can detect anomalies by projecting the measured traffic data onto a normal and anomalous subspaces. In the classical PCA-based anomaly detection scheme, however, outliers, anomalies with excessively large traffic volume, may degrade its performance, which is referred to as the subspace contamination problem. In this article, we propose a new traffic anomaly detection scheme based on the MCD (Minimum Covariance Detection) scheme, a robust PCA mechanism. The proposed scheme utilizes the periodicity of network traffic, and before constructing subspaces, outliers are removed by using the measured traffic in the preceding period. Although robust PCA schemes are effective against the subspace contamination problem themselves, the proposed scheme can reduce the computational cost by using the traffic periodicity. We evaluate the performance of the proposed scheme with numerical experiments. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Traffic Anomaly Detection / Principal Component Analysis / Periodicity of network traffic / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 113, no. 292, NS2013-128, pp. 71-76, Nov. 2013. | |
| Paper # | NS2013-128 | |
| Date of Issue | 2013-11-07 (NS) | |
| ISSN | Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | NS2013-128 |
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| Conference Information | |
| Committee | NS CQ ICM NV |
| Conference Date | 2013-11-14 - 2013-11-15 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Goto Islands |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Network Quality, Network Measurement and Management, Network Virtualization, Network Service, General |
| Paper Information | |
| Registration To | NS |
| Conference Code | 2013-11-NS-CQ-ICM |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Robust Principal Component Analysis for Traffic Anomaly Detection |
| Sub Title (in English) | |
| Keyword(1) | Traffic Anomaly Detection |
| Keyword(2) | Principal Component Analysis |
| Keyword(3) | Periodicity of network traffic |
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| 1st Author's Name | Takahiro Matsuda |
| 1st Author's Affiliation | Osaka University (Osaka Univ.) |
| 2nd Author's Name | Tatsuya Morita |
| 2nd Author's Affiliation | Osaka University (Osaka Univ.) |
| 3rd Author's Name | Takanori Kudo |
| 3rd Author's Affiliation | Osaka University (Osaka Univ.) |
| 4th Author's Name | Tetsuya Takine |
| 4th Author's Affiliation | Osaka University (Osaka Univ.) |
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| Speaker | Author-1 |
| Date Time | 2013-11-15 13:30:00 |
| Presentation Time | 25 minutes |
| Registration for | NS |
| Paper # | NS2013-128 |
| Volume (vol) | vol.113 |
| Number (no) | no.292 |
| Page | pp.71-76 |
| #Pages | 6 |
| Date of Issue | 2013-11-07 (NS) |
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