Paper Abstract and Keywords |
Presentation |
2016-11-04 10:35
Deep Learning for Ransomware Detection Aragorn Tseng, YunChun Chen, YiHsiang Kao, Tsungnan Lin (NTU) IA2016-46 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Ransomware is malware that installs covertly on a victim's computer or smartphone, executes a cryptovirology attack and demands a ransom payment to restore it. Ransomwares have been the most serious threat in 2016, and this situation continues to worsen. Because of high reward for Ransomwares, more and more Ransomware families appear, and it make us more difficultly to detect them. There are different signatures or behaviors among different families (i.e. Locky ,Cerber,Cryptowall .....)or versions (i.e. CryptXXX2.0 ,CryptXXX3.0) of Ransomwares, it will be wonderful if there has a way that can detect potential Ransomware threats.
In this paper, we use deep-learning method to detect Ransomwares. At first we introduce how we label the data with different behaviors and what features we choose. And we present our model for detecting various Ransomwares and prevent them from encrypting victim's data. Experimental evaluation demonstrates that our deep-learning model can detect latest Ransomwares in high-speed network timely. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Ransomware / deep-learning / cyber-attack / machine-learning / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 116, no. 282, IA2016-46, pp. 87-92, Nov. 2016. |
Paper # |
IA2016-46 |
Date of Issue |
2016-10-27 (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) |
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IA2016-46 |
Conference Information |
Committee |
IA |
Conference Date |
2016-11-03 - 2016-11-04 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Taipei (Taiwan) |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
IA2016 - Workshop on Internet Architecture and Applications 2016 |
Paper Information |
Registration To |
IA |
Conference Code |
2016-11-IA |
Language |
English |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Deep Learning for Ransomware Detection |
Sub Title (in English) |
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Ransomware |
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deep-learning |
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cyber-attack |
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machine-learning |
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1st Author's Name |
Aragorn Tseng |
1st Author's Affiliation |
National Taiwan University (NTU) |
2nd Author's Name |
YunChun Chen |
2nd Author's Affiliation |
National Taiwan University (NTU) |
3rd Author's Name |
YiHsiang Kao |
3rd Author's Affiliation |
National Taiwan University (NTU) |
4th Author's Name |
Tsungnan Lin |
4th Author's Affiliation |
National Taiwan University (NTU) |
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Speaker |
Author-1 |
Date Time |
2016-11-04 10:35:00 |
Presentation Time |
20 minutes |
Registration for |
IA |
Paper # |
IA2016-46 |
Volume (vol) |
vol.116 |
Number (no) |
no.282 |
Page |
pp.87-92 |
#Pages |
6 |
Date of Issue |
2016-10-27 (IA) |
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