Paper Abstract and Keywords |
Presentation |
2019-03-05 13:30
Analytics for LAN Traffic Data using Deep Learning Yuwei Sun, Hideya Ochiai, Hiroshi Esaki (UTokyo) NS2018-269 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In recent years, because Deep Learning algorithm can automatically learn the features from the training set, it has received extensive attention in many fields. Compared to the machine learning algorithms so far, it has greatly improved the expressiveness in these fields. On the other hand, in this era of Information communication, the task of security in the network has become more and more difficult to deal with. However, events occurring in the network are still not transparent enough to know the high-level information hidden in the big data of network transportation, which actually contains a great deal of risk. In this research, we propose a method to classify events using deep learning, CNN (Convocational Neural Network) based on feature maps created from traffic data in the network. In this paper, we focus on the feature expression of the traffic data in LAN and the applicability of deep learning to network security task. In this research, we propose a method, constantly monitoring activities in the LAN, and detecting malware intrusions, malicious intrusions that target devices in the LAN, using an approach of deep learning. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
deep learning / security / LAN / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 465, NS2018-269, pp. 443-448, March 2019. |
Paper # |
NS2018-269 |
Date of Issue |
2019-02-25 (NS) |
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) |
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NS2018-269 |
Conference Information |
Committee |
IN NS |
Conference Date |
2019-03-04 - 2019-03-05 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Okinawa Convention Center |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
General |
Paper Information |
Registration To |
NS |
Conference Code |
2019-03-IN-NS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
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(See Japanese page) |
Title (in English) |
Analytics for LAN Traffic Data using Deep Learning |
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deep learning |
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security |
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LAN |
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1st Author's Name |
Yuwei Sun |
1st Author's Affiliation |
The University of Tokyo (UTokyo) |
2nd Author's Name |
Hideya Ochiai |
2nd Author's Affiliation |
The University of Tokyo (UTokyo) |
3rd Author's Name |
Hiroshi Esaki |
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The University of Tokyo (UTokyo) |
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Speaker |
Author-1 |
Date Time |
2019-03-05 13:30:00 |
Presentation Time |
20 minutes |
Registration for |
NS |
Paper # |
NS2018-269 |
Volume (vol) |
vol.118 |
Number (no) |
no.465 |
Page |
pp.443-448 |
#Pages |
6 |
Date of Issue |
2019-02-25 (NS) |
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