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 |
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) |
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SIP2017-52 |
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) |
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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) |
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Keyword(1) |
DDoS attack detection |
Keyword(2) |
Extended OD flow matrix |
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Group Sparsitiy |
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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 |
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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 |
6 |
Date of Issue |
2017-08-17 (SIP) |
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