Paper Abstract and Keywords |
Presentation |
2018-11-22 13:55
Individuality Extraction from Flick Action Trajectory for Personal Identification on Smartphones Masashi Sekikawa, Yuta Ozawa, Kohei Minemura, Masaki Kyoso (TCU) MBE2018-43 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Latest smartphones which have many functions deal with many personal information. Therefore, advanced security measures are required. As a conventional security countermeasure, fingerprints and face authentications using passwords, pattern inputs, physical features of biometric authentication are mainstream. However, there are problems that passwords and pattern inputs are weak against peeps and brute force method / brute force attack, biometric authentication such as fingerprints can be copied and unconscious authentication is difficult. Therefore, in this research, we propose an authentication method for flick operation on smartphone focusing on behavioral features of biometric authentication. Trajectory data from the start to the end of the touch was acquired for 10 subjects by the measurement application from the flick operation. And we performed individual identification by neural network. By discriminating between the vertical direction vertical coordinate and the lateral direction horizontal coordinate, it was possible to obtain an identification rate of 34 to 100% as the discrimination rate. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Biometrics / Smartphone / Flick Action / Trajectory / Personal Identification / Neural Network / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 321, MBE2018-43, pp. 35-39, Nov. 2018. |
Paper # |
MBE2018-43 |
Date of Issue |
2018-11-15 (MBE) |
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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MBE2018-43 |
Conference Information |
Committee |
MBE NC |
Conference Date |
2018-11-22 - 2018-11-22 |
Place (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
MBE |
Conference Code |
2018-11-MBE-NC |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Individuality Extraction from Flick Action Trajectory for Personal Identification on Smartphones |
Sub Title (in English) |
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Keyword(1) |
Biometrics |
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Smartphone |
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Flick Action |
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Trajectory |
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Personal Identification |
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Neural Network |
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1st Author's Name |
Masashi Sekikawa |
1st Author's Affiliation |
Tokyo City University (TCU) |
2nd Author's Name |
Yuta Ozawa |
2nd Author's Affiliation |
Tokyo City University (TCU) |
3rd Author's Name |
Kohei Minemura |
3rd Author's Affiliation |
Tokyo City University (TCU) |
4th Author's Name |
Masaki Kyoso |
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Tokyo City University (TCU) |
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Speaker |
Author-1 |
Date Time |
2018-11-22 13:55:00 |
Presentation Time |
25 minutes |
Registration for |
MBE |
Paper # |
MBE2018-43 |
Volume (vol) |
vol.118 |
Number (no) |
no.321 |
Page |
pp.35-39 |
#Pages |
5 |
Date of Issue |
2018-11-15 (MBE) |
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