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Paper Abstract and Keywords
Presentation 2018-11-21 14:50
Spoofed Website Detection using Machine Learning
Naoki Kurihara, Hidenori Tsuji, Masaki Hashimoto (Institute of Information Security) ICSS2018-56
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, the damage by fake site has been rapidly increasing. Because fake sites are ceremonious as if they are genuine, it is difficult to simply detect a fake site, and in the present situation, because humans are conducting surveys one by one for many sites that exist , It takes a considerable amount of time to detect fake sites. In this research, in order to solve this problem, by developing a fake site detection method using machine learning, it is possible to automate the detection process reliant on human hands to some extent and shorten the time taken for fake site detection aim. In this paper, for this purpose, we present the current status and problems of fake site detection and report the result of two experiments for developing new method.
Keyword (in Japanese) (See Japanese page) 
(in English) HTML / Machine Learning / Support Vector Machine / Multilayer Perceptron / Spoofed Website / Natural language processing / doc2vec /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 315, ICSS2018-56, pp. 19-24, Nov. 2018.
Paper # ICSS2018-56 
Date of Issue 2018-11-14 (ICSS) 
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 ICSS2018-56

Conference Information
Committee ICSS  
Conference Date 2018-11-21 - 2018-11-22 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To ICSS 
Conference Code 2018-11-ICSS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Spoofed Website Detection using Machine Learning 
Sub Title (in English)  
Keyword(1) HTML  
Keyword(2) Machine Learning  
Keyword(3) Support Vector Machine  
Keyword(4) Multilayer Perceptron  
Keyword(5) Spoofed Website  
Keyword(6) Natural language processing  
Keyword(7) doc2vec  
Keyword(8)  
1st Author's Name Naoki Kurihara  
1st Author's Affiliation Institute of Information Security (Institute of Information Security)
2nd Author's Name Hidenori Tsuji  
2nd Author's Affiliation Institute of Information Security (Institute of Information Security)
3rd Author's Name Masaki Hashimoto  
3rd Author's Affiliation Institute of Information Security (Institute of Information Security)
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Speaker Author-1 
Date Time 2018-11-21 14:50:00 
Presentation Time 25 minutes 
Registration for ICSS 
Paper # ICSS2018-56 
Volume (vol) vol.118 
Number (no) no.315 
Page pp.19-24 
#Pages 6 
Date of Issue 2018-11-14 (ICSS) 

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