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Paper Abstract and Keywords
Presentation 2026-07-23 09:00
[Poster Presentation] The Impact of the Coexistence of Scale-Free and Clustering Properties on Network Anomaly Detection
Koki Kampu, Yusuke Sakumoto (Kwansei Gakuin Univ.) CQ2026-36
Abstract (in Japanese) (See Japanese page) 
(in English) Real-world network systems change their structures over time, and early detection of anomalous changes in such networks is an important problem. As anomaly detection methods for dynamic networks, LAD, which uses the largest eigenvalues of the Laplacian matrix, has been proposed. As an extension of LAD, we have proposed eLAD, which uses not only the largest eigenvalues but also the smallest eigenvalues. Furthermore, eLAD+GSS has been proposed as a method for determining the ratio of the largest and smallest eigenvalues used in eLAD based on GSS (Graph Spectrum Shift). However, it has not been fully clarified whether eigenvalue selection by eLAD+GSS works effectively for networks in which scale-free and clustering properties coexist. Therefore, in this paper, we generate dynamic networks using the LM model and evaluate the effectiveness of eLAD+GSS for networks in which scale-free and clustering properties coexist. The evaluation results show that, in LM networks with both scale-free and clustering properties, multiple peaks appear in the eigenvalue distribution of the Laplacian matrix, and thus the detection success rate does not sufficiently improve when the Laplacian matrix is used. On the other hand, we confirm that the detection success rate improves when the normalized Laplacian matrix is used.
Keyword (in Japanese) (See Japanese page) 
(in English) Anomaly Detection / Dynamic Network / Spectral Graph Theory / Laplacian Matrix / Low-Rank Approximation / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 121, CQ2026-36, pp. 126-131, July 2026.
Paper # CQ2026-36 
Date of Issue 2026-07-14 (CQ) 
ISSN 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 CQ2026-36

Conference Information
Committee CQ  
Conference Date 2026-07-21 - 2026-07-23 
Place (in Japanese) (See Japanese page) 
Place (in English) Eef Jouhou Plaza 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To CQ 
Conference Code 2026-07-CQ 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) The Impact of the Coexistence of Scale-Free and Clustering Properties on Network Anomaly Detection 
Sub Title (in English)  
Keyword(1) Anomaly Detection  
Keyword(2) Dynamic Network  
Keyword(3) Spectral Graph Theory  
Keyword(4) Laplacian Matrix  
Keyword(5) Low-Rank Approximation  
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1st Author's Name Koki Kampu  
1st Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ.)
2nd Author's Name Yusuke Sakumoto  
2nd Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ.)
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Speaker Author-1 
Date Time 2026-07-23 09:00:00 
Presentation Time 60 minutes 
Registration for CQ 
Paper # CQ2026-36 
Volume (vol) vol.126 
Number (no) no.121 
Page pp.126-131 
#Pages 6 
Date of Issue 2026-07-14 (CQ) 

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