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Paper Abstract and Keywords
Presentation 2008-12-12 14:55
An Automatic and Dynamic Parameter Tuning of a Statistics-based Network Anomaly Detection Algorithm
Yosuke Himura (the Univ. of Tokyo), Kensuke Fukuda (NII/PRESTO, JST), Kenjiro Cho (Internet Initiative Japan), Hiroshi Esaki (the Univ. of Tokyo) IN2008-106
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we investigate an automatic and dynamic parameter tuning method of a statistical network traffic anomaly detection algorithm. We evaluate the appropriate learning period of parameter setting in anomaly detection algorithm based on sketch and multi-scale gamma-function model with real network traces measured for 7 months. The main results are following: (1) Without learning, the best parameter highly varies day by day. (2) With a longer learning period, the best parameter setting is affected by significant data during the larning period. (3) The appropriate period of the learning is around 3 days. (4) The performance degradation rate with dynamic parameter tuning is 17% in the best case.
Keyword (in Japanese) (See Japanese page) 
(in English) traffic analysis / anomaly detection / performance evaluation / dynamic parameter optimization / / / /  
Reference Info. IEICE Tech. Rep., vol. 108, no. 342, IN2008-106, pp. 121-126, Dec. 2008.
Paper # IN2008-106 
Date of Issue 2008-12-04 (IN) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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)
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Conference Information
Committee IN  
Conference Date 2008-12-11 - 2008-12-12 
Place (in Japanese) (See Japanese page) 
Place (in English) Hiroshima City University 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IN 
Conference Code 2008-12-IN 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An Automatic and Dynamic Parameter Tuning of a Statistics-based Network Anomaly Detection Algorithm 
Sub Title (in English)  
Keyword(1) traffic analysis  
Keyword(2) anomaly detection  
Keyword(3) performance evaluation  
Keyword(4) dynamic parameter optimization  
1st Author's Name Yosuke Himura  
1st Author's Affiliation the University of Tokyo (the Univ. of Tokyo)
2nd Author's Name Kensuke Fukuda  
2nd Author's Affiliation National Institute of Informatics/Japan Science and Technology Agency PRESTO (NII/PRESTO, JST)
3rd Author's Name Kenjiro Cho  
3rd Author's Affiliation Internet Initiative Japan (Internet Initiative Japan)
4th Author's Name Hiroshi Esaki  
4th Author's Affiliation the University of Tokyo (the Univ. of Tokyo)
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Speaker Author-1 
Date Time 2008-12-12 14:55:00 
Presentation Time 25 minutes 
Registration for IN 
Paper # IN2008-106 
Volume (vol) vol.108 
Number (no) no.342 
Page pp.121-126 
Date of Issue 2008-12-04 (IN) 

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