Paper Abstract and Keywords |
Presentation |
2019-03-04 09:00
Intrusion Detection System using semi-supervised learning with Adversarial Autoencoder Kazuki Hara, Kohei Shiomoto (Tokyo City Univ.) NS2018-193 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In recent years the importance of intrusion detection system(IDS) is increasing. In particular, a method using machine learning has attracted attention. However, supervised learning to achieve high detection accuracy is expensive because it requires large amount of training data. As new attacks are constantly born, it is necessary to continuously update IDS with new training data. However it is difficult to keep large amount of training data. To address the issue, we propose a semi-supervised learning method using Adversarial Autoencoder. We evaluate the effectiveness of the proposed method using NSL-KDD dataset. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Intrusion Detection System / Machine learning / Semi-supervised learning / Adversarial Autoencoder / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 465, NS2018-193, pp. 1-6, March 2019. |
Paper # |
NS2018-193 |
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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NS2018-193 |
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 |
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(See Japanese page) |
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General |
Paper Information |
Registration To |
NS |
Conference Code |
2019-03-IN-NS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Intrusion Detection System using semi-supervised learning with Adversarial Autoencoder |
Sub Title (in English) |
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Intrusion Detection System |
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Machine learning |
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Semi-supervised learning |
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Adversarial Autoencoder |
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1st Author's Name |
Kazuki Hara |
1st Author's Affiliation |
Tokyo City University (Tokyo City Univ.) |
2nd Author's Name |
Kohei Shiomoto |
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Tokyo City University (Tokyo City Univ.) |
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Speaker |
Author-1 |
Date Time |
2019-03-04 09:00:00 |
Presentation Time |
20 minutes |
Registration for |
NS |
Paper # |
NS2018-193 |
Volume (vol) |
vol.118 |
Number (no) |
no.465 |
Page |
pp.1-6 |
#Pages |
6 |
Date of Issue |
2019-02-25 (NS) |
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