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Paper Abstract and Keywords
Presentation 2021-06-24 13:45
Privacy-Preserving Secure Computation of Gaussian Process Regression -- Find patterns and rules from encrypted data --
Takayuki Nakachi (Univ. of the Ryukyus), Yitu Wang (NTT) SIS2021-8
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we propose Gaussian Process Regression (GPR) for encrypted data generated based on random unitary transformation and evaluate its performance. In recent years, computational forms that utilize computational resources provided by providers using edge and cloud services have rapidly become widespread. However, there are concerns about problems such as data fraud, leakage, and privacy invasion due to lack of reliability of providers and accidents. This paper examines the secure Gaussian process regression method that takes privacy protection into consideration. It is shown that the secure operation is established even when there is a non-linear relationship between the input data and the output data. Finally, as an application example of the secure Gaussian process regression, the disease progression is predicted using clinical data of diabetes, and the effectiveness of the proposed method is verified by simulation.
Keyword (in Japanese) (See Japanese page) 
(in English) Machine Learning / Gaussian Process / Random Unitary Transformation / Secure Computation / Edge/Cloud Computing / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 73, SIS2021-8, pp. 43-48, June 2021.
Paper # SIS2021-8 
Date of Issue 2021-06-17 (SIS) 
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 SIS2021-8

Conference Information
Committee SIS IPSJ-AVM  
Conference Date 2021-06-24 - 2021-06-24 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Intelligent Multimedia Systems, Applied Embedded Systems, Three-Dimensional Image Technology (3DIT), etc. 
Paper Information
Registration To SIS 
Conference Code 2021-06-SIS-AVM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Privacy-Preserving Secure Computation of Gaussian Process Regression 
Sub Title (in English) Find patterns and rules from encrypted data 
Keyword(1) Machine Learning  
Keyword(2) Gaussian Process  
Keyword(3) Random Unitary Transformation  
Keyword(4) Secure Computation  
Keyword(5) Edge/Cloud Computing  
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Keyword(7)  
Keyword(8)  
1st Author's Name Takayuki Nakachi  
1st Author's Affiliation University of the Ryukyus (Univ. of the Ryukyus)
2nd Author's Name Yitu Wang  
2nd Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
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Speaker Author-1 
Date Time 2021-06-24 13:45:00 
Presentation Time 20 minutes 
Registration for SIS 
Paper # SIS2021-8 
Volume (vol) vol.121 
Number (no) no.73 
Page pp.43-48 
#Pages 6 
Date of Issue 2021-06-17 (SIS) 

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