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| Paper Abstract and Keywords | ||
| Presentation | 2022-12-21 17:10 An Algorithm Combined Grouping and Adding Dummy to Satisfy l-diversity Keiichiro Oishi, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga (UEC)  AI2022-47 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Universities and companies access personal information databases for a wide range of purposes, and privacy considerations must be taken into account when using such databases. Most of the existing anonymization technologies excludes identifiers that uniquely identify individuals and process quasi-identifiers (QIDs), which do not uniquely identify an individual but are well-correlated with that individual. Here we propose an anonymization algorithm based on a non-processing method for QIDs called the dummy record %addition method, and this algorithm succussed reduces the number of dummy records added for anonymization. A verification experiment confirmed a more balanced safety-usefulness tradeoff in the proposed algorithm than in %comparative existing technologies while maintaining the $l$-diversity, a main indicator of privacy security. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | l-diversity / Dummy / Privacy Preserving Data Mining / Privacy Preserving Data Publishing / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 322, AI2022-47, pp. 80-86, Dec. 2022. | |
| Paper # | AI2022-47 | |
| Date of Issue | 2022-12-14 (AI) | |
| 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 | AI2022-47 |
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| Conference Information | |
| Committee | AI |
| Conference Date | 2022-12-21 - 2022-12-21 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | AI |
| Conference Code | 2022-12-AI |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | An Algorithm Combined Grouping and Adding Dummy to Satisfy l-diversity |
| Sub Title (in English) | |
| Keyword(1) | l-diversity |
| Keyword(2) | Dummy |
| Keyword(3) | Privacy Preserving Data Mining |
| Keyword(4) | Privacy Preserving Data Publishing |
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| 1st Author's Name | Keiichiro Oishi |
| 1st Author's Affiliation | The University of Electro-Communications (UEC) |
| 2nd Author's Name | Yuichi Sei |
| 2nd Author's Affiliation | The University of Electro-Communications (UEC) |
| 3rd Author's Name | Yasuyuki Tahara |
| 3rd Author's Affiliation | The University of Electro-Communications (UEC) |
| 4th Author's Name | Akihiko Ohsuga |
| 4th Author's Affiliation | The University of Electro-Communications (UEC) |
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| Speaker | Author-1 |
| Date Time | 2022-12-21 17:10:00 |
| Presentation Time | 20 minutes |
| Registration for | AI |
| Paper # | AI2022-47 |
| Volume (vol) | vol.122 |
| Number (no) | no.322 |
| Page | pp.80-86 |
| #Pages | 7 |
| Date of Issue | 2022-12-14 (AI) |
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