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Paper Abstract and Keywords
Presentation 2023-04-14 11:40
Network Anomaly Detection through Variable Granularity Traffic Analysis
Shohei Kamamura, Yuya Takeda (Seikei Univ.), Yuki Takei, Masato Nishiguchi, Yuhei Hayashi, Takayuki Fujiwara (NTT) NS2023-9
Abstract (in Japanese) (See Japanese page) 
(in English) In the Society 5.0, it is important to accurately measure and analyze the communication traffic flow in wide-area IP networks, and to be able to promptly detect communication anomalies for achieving sustainable social infrastructure. However, in wide-area IP networks, communication traffic flow is encapsulated by headers assigned by communication carriers, and thus is observed as more macroscopic information. Therefore, it is difficult to accurately detect the occurrence of anomalies for an individual communication flow because the flow observation results obtained by flow measurement protocols such as IPFIX are the result of superimposing various communication flows with different characteristics. In this paper, we propose a method of anomaly analysis and detection method from time-series traffic flows. First, we decompose superimposing traffic flows into individual flows by using our implementation of the Fast xFlow Proxy, which can decompose communication traffic flows to a fine granularity. Then, our algorithm detects anomalies from decomposed flows based on correlation analysis. We report the results of a simulation evaluation of the proposed method, which shows that it can achieve anomaly detection quickly and accurately.
Keyword (in Japanese) (See Japanese page) 
(in English) IP Network, / xFlow / Communication Traffic / Correlation Analysis / Anomaly Detection / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 2, NS2023-9, pp. 44-49, April 2023.
Paper # NS2023-9 
Date of Issue 2023-04-06 (NS) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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 NS2023-9

Conference Information
Committee NS  
Conference Date 2023-04-13 - 2023-04-14 
Place (in Japanese) (See Japanese page) 
Place (in English) Nihon University, Koriyama Campus + Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Communication traffic theory, Traffic and quality evaluation, Network performance evaluation, QoS/QoE, Reliability and robustness, Traffic and quality management, AI and machine learning, Network and system operation management, High capacity, low latency, many connections, General 
Paper Information
Registration To NS 
Conference Code 2023-04-NS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Network Anomaly Detection through Variable Granularity Traffic Analysis 
Sub Title (in English)  
Keyword(1) IP Network,  
Keyword(2) xFlow  
Keyword(3) Communication Traffic  
Keyword(4) Correlation Analysis  
Keyword(5) Anomaly Detection  
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1st Author's Name Shohei Kamamura  
1st Author's Affiliation Seikei University (Seikei Univ.)
2nd Author's Name Yuya Takeda  
2nd Author's Affiliation Seikei University (Seikei Univ.)
3rd Author's Name Yuki Takei  
3rd Author's Affiliation NTT Network Innovation Center (NTT)
4th Author's Name Masato Nishiguchi  
4th Author's Affiliation NTT Network Innovation Center (NTT)
5th Author's Name Yuhei Hayashi  
5th Author's Affiliation NTT Network Innovation Center (NTT)
6th Author's Name Takayuki Fujiwara  
6th Author's Affiliation NTT Network Innovation Center (NTT)
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Speaker Author-1 
Date Time 2023-04-14 11:40:00 
Presentation Time 25 minutes 
Registration for NS 
Paper # NS2023-9 
Volume (vol) vol.123 
Number (no) no.2 
Page pp.44-49 
#Pages
Date of Issue 2023-04-06 (NS) 


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