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Paper Abstract and Keywords
Presentation 2017-08-24 14:15
A DDoS Attack Detection Based on Group Sparsities of OD Flow Matrices
Masaya Endo, Masao Yamagishi, Isao Yamada (Tokyo Inst. of Tech.) SIP2017-52
Abstract (in Japanese) (See Japanese page) 
(in English) To realize effective detection schemes applicable to diverse network traffic anomalies, we first propose to use group sparsities of the {em extended OD flow matrix}, expressing time transitions of traffic matrices, for flexible characterizations of major pathological behaviors of network traffic. We also formulate an approximate decomposition problem of an extended OD flow matrix into a group sparse and a low-rank matrix, and show that this problem, {em generalized robust principal component analysis for anormaly detection}, can be solved by efficiently with proximal splitting methods. Moreover, we present a novel characterization of typical DDoS (Distributed Denial of Service) attacks with a certain sparsity of OD flows after being assigned to groups of the same destinations.
The proposed characterization is combined with the generalized robust principal component analysis to establish a DDoS attack detection scheme.
Numerical experiments demonstrate effectiveness of the proposed DDoS attack detection scheme.
Keyword (in Japanese) (See Japanese page) 
(in English) DDoS attack detection / Extended OD flow matrix / Group Sparsitiy / Generalized robust principal component analysis / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 180, SIP2017-52, pp. 21-26, Aug. 2017.
Paper # SIP2017-52 
Date of Issue 2017-08-17 (SIP) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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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 SIP  
Conference Date 2017-08-24 - 2017-08-25 
Place (in Japanese) (See Japanese page) 
Place (in English) Tokyo Denki University 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SIP 
Conference Code 2017-08-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A DDoS Attack Detection Based on Group Sparsities of OD Flow Matrices 
Sub Title (in English)  
Keyword(1) DDoS attack detection  
Keyword(2) Extended OD flow matrix  
Keyword(3) Group Sparsitiy  
Keyword(4) Generalized robust principal component analysis  
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1st Author's Name Masaya Endo  
1st Author's Affiliation Tokyo Institute of Technology (Tokyo Inst. of Tech.)
2nd Author's Name Masao Yamagishi  
2nd Author's Affiliation Tokyo Institute of Technology (Tokyo Inst. of Tech.)
3rd Author's Name Isao Yamada  
3rd Author's Affiliation Tokyo Institute of Technology (Tokyo Inst. of Tech.)
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Speaker Author-1 
Date Time 2017-08-24 14:15:00 
Presentation Time 25 minutes 
Registration for SIP 
Paper # SIP2017-52 
Volume (vol) vol.117 
Number (no) no.180 
Page pp.21-26 
#Pages
Date of Issue 2017-08-17 (SIP) 


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