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Paper Abstract and Keywords
Presentation 2024-01-16 15:25
[Invited Talk] Federated Learning with Enhanced Privacy Protection in AI
Lihua Wang (NICT) EMM2023-83
Abstract (in Japanese) (See Japanese page) 
(in English) Federated learning is a crucial methodology in artificial intelligence where multiple organizations collaborate to perform machine learning on overall data without sharing the data itself. In this talk, we identify challenges in federated learning that are becoming increasingly important, specifically the potential for information leakage. We introduce privacy protection frameworks to address this issue. The proposed frameworks are applicable to existing federated learning systems, including deep learning and gradient boosting decision trees, to safeguard privacy. We also discuss relevant research, recent developments in practical applications, and future prospects in this field.
Keyword (in Japanese) (See Japanese page) 
(in English) Federated learning / privacy preservation / Homomorphic Encryption / deep learning / decision tree / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 332, EMM2023-83, pp. 19-19, Jan. 2024.
Paper # EMM2023-83 
Date of Issue 2024-01-09 (EMM) 
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 EMM2023-83

Conference Information
Committee EMM  
Conference Date 2024-01-16 - 2024-01-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Tohoku Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Sense of Presence, Universal Media, Digital Entertainment, etc. 
Paper Information
Registration To EMM 
Conference Code 2024-01-EMM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Federated Learning with Enhanced Privacy Protection in AI 
Sub Title (in English)  
Keyword(1) Federated learning  
Keyword(2) privacy preservation  
Keyword(3) Homomorphic Encryption  
Keyword(4) deep learning  
Keyword(5) decision tree  
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1st Author's Name Lihua Wang  
1st Author's Affiliation NICT Cybersecurity Research Institute (NICT)
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Speaker Author-1 
Date Time 2024-01-16 15:25:00 
Presentation Time 50 minutes 
Registration for EMM 
Paper # EMM2023-83 
Volume (vol) vol.123 
Number (no) no.332 
Page p.19 
#Pages 1 
Date of Issue 2024-01-09 (EMM) 

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