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Paper Abstract and Keywords
Presentation 2017-11-15 13:50
Machine Learning Approach for Phishing Detection in SDN Networking
Yu-Hung Chen, Jiun-Yu Yang, Po-Chun Hou, Jiann-Liang Chen (National Taiwan University of Science & Technology) IA2017-30
Abstract (in Japanese) (See Japanese page) 
(in English) People have become increasingly dependent on information technology since the emergence of the Internet. Therefore, many hackers engage in financial crimes and computer attacks through the Internet. The existing attack modes include a combination of Trojans, Botnet, social engineering, and email phishing technology. In recent years, the rise of numerous phishing attacks has led to great money loss on the part of people deceived by phishing attacks. In general, phishing websites have a short lifetime, and the attack technique is relatively more complex, thus drawing information security concern. In this study, the software-defined infrastructure was adopted to deploy a platform where automated phishing website risk analysis, assessment, and strategic executions and operations were conducted. During the experimentation period, 25,000 phishing websites were obtained using Common Crawl, and 25,000 illegal websites were obtained from Phishing Tank. Machine learning was conjunctively used in this study to complete the research and development of the phishing website learning model creation, risk analysis, hazard assessment, and other mechanisms. Software-defined networking was subsequently used to carry out strategic execution targeting hazardous messages in order to ensure a high degree of overall network environment security. The experimental results show that the training model in this study reaches an accuracy of 96.97%.
Keyword (in Japanese) (See Japanese page) 
(in English) Phishing detection / Software-Defined Networking / Extreme Learning Machine / Ensemble Learning / Feature engineering / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 299, IA2017-30, pp. 1-6, Nov. 2017.
Paper # IA2017-30 
Date of Issue 2017-11-08 (IA) 
ISSN Print edition: ISSN 0913-5685    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 IA2017-30

Conference Information
Committee IA  
Conference Date 2017-11-15 - 2017-11-16 
Place (in Japanese) (See Japanese page) 
Place (in English) KMITL, Bangkok, Thailand 
Topics (in Japanese) (See Japanese page) 
Topics (in English) IA2017 - Workshop on Internet Architecture and Applications 2017 
Paper Information
Registration To IA 
Conference Code 2017-11-IA 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Machine Learning Approach for Phishing Detection in SDN Networking 
Sub Title (in English)  
Keyword(1) Phishing detection  
Keyword(2) Software-Defined Networking  
Keyword(3) Extreme Learning Machine  
Keyword(4) Ensemble Learning  
Keyword(5) Feature engineering  
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Keyword(7)  
Keyword(8)  
1st Author's Name Yu-Hung Chen  
1st Author's Affiliation National Taiwan University of Science & Technology (National Taiwan University of Science & Technology)
2nd Author's Name Jiun-Yu Yang  
2nd Author's Affiliation National Taiwan University of Science & Technology (National Taiwan University of Science & Technology)
3rd Author's Name Po-Chun Hou  
3rd Author's Affiliation National Taiwan University of Science & Technology (National Taiwan University of Science & Technology)
4th Author's Name Jiann-Liang Chen  
4th Author's Affiliation National Taiwan University of Science & Technology (National Taiwan University of Science & Technology)
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Speaker Author-1 
Date Time 2017-11-15 13:50:00 
Presentation Time 25 minutes 
Registration for IA 
Paper # IA2017-30 
Volume (vol) vol.117 
Number (no) no.299 
Page pp.1-6 
#Pages 6 
Date of Issue 2017-11-08 (IA) 

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