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Paper Abstract and Keywords
Presentation 2021-01-22 14:20
An Aggregation Approach for Improving Network Scan Failure and Delay Estimation of IoT Wireless Equipment
Babatunde Ojetunde, Kenta Suzuki, Kazuto Yano, Yoshinori Suzuki (ATR) NS2020-118
Abstract (in Japanese) (See Japanese page) 
(in English) Recently we proposed a method for identifying the network scan response state that is needed to estimate the cause of network scan failure/delay which is necessary in detecting vulnerable IoT wireless device. However, there are cases in which the cause of scan failure/delay algorithm fails to correctly judge the cause of failure/delay of newly acquire scan response data as a result of wrong identification. Therefore an approach that can improve the identification of network scan response data and the cause of scan failure/delay estimation in all situations is required. This paper proposes an aggregation method which is needed to improve the network state identification and the estimation of the cause of scan failure/delay of the IoT wireless device. Specifically, we identify and correctly estimate the scan response data, preliminary obtained in various network states (i.e., Normal, Low-SNR, and Congestion) and the newly acquired scan response data. Thereafter, an aggregation by concatenation is performed on the scan response data that is identified to belong to the same network state and the aggregated sample is utilized as part of the sample used in the subsequent identification and estimation of other scan response samples. The evaluation results show that the proposed aggregation method improves the correct identification of the scan response network state and achieved a 99% correct estimation results of the cause of scan failure/delay when compared to our previous method without the aggregation method.
Keyword (in Japanese) (See Japanese page) 
(in English) Network scan / IoT / cyber-attacks / machine learning / similarity / aggregation / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 327, NS2020-118, pp. 43-52, Jan. 2021.
Paper # NS2020-118 
Date of Issue 2021-01-14 (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)
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Conference Information
Committee NS NWS  
Conference Date 2021-01-21 - 2021-01-22 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Network software (Software architecture, Middleware), Network application, SOA/SDP, NGN/IMS/API, Distributed control/Dynamic routing, Grid, NFV, IoT, Network/System reliability, Network/System evaluation, etc. 
Paper Information
Registration To NS 
Conference Code 2021-01-NS-NWS 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An Aggregation Approach for Improving Network Scan Failure and Delay Estimation of IoT Wireless Equipment 
Sub Title (in English)  
Keyword(1) Network scan  
Keyword(2) IoT  
Keyword(3) cyber-attacks  
Keyword(4) machine learning  
Keyword(5) similarity  
Keyword(6) aggregation  
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Keyword(8)  
1st Author's Name Babatunde Ojetunde  
1st Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
2nd Author's Name Kenta Suzuki  
2nd Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
3rd Author's Name Kazuto Yano  
3rd Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
4th Author's Name Yoshinori Suzuki  
4th Author's Affiliation Advanced Telecommunications Research Institute International (ATR)
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Speaker Author-1 
Date Time 2021-01-22 14:20:00 
Presentation Time 25 minutes 
Registration for NS 
Paper # NS2020-118 
Volume (vol) vol.120 
Number (no) no.327 
Page pp.43-52 
#Pages 10 
Date of Issue 2021-01-14 (NS) 


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