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Utility–Privacy Trade-Offs with Limited Leakage for Encoder

The utilization of databases such as IoT has progressed, and understanding how to protect the privacy of data is an important issue. As pioneering work, in 1983, Yamamoto assumed the source (database), which consists of public information and private information, and found theoretical limits (first-...

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Autores principales: Shinohara, Naruki, Yagi, Hideki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10297384/
https://www.ncbi.nlm.nih.gov/pubmed/37372265
http://dx.doi.org/10.3390/e25060921
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author Shinohara, Naruki
Yagi, Hideki
author_facet Shinohara, Naruki
Yagi, Hideki
author_sort Shinohara, Naruki
collection PubMed
description The utilization of databases such as IoT has progressed, and understanding how to protect the privacy of data is an important issue. As pioneering work, in 1983, Yamamoto assumed the source (database), which consists of public information and private information, and found theoretical limits (first-order rate analysis) among the coding rate, utility and privacy for the decoder in two special cases. In this paper, we consider a more general case based on the work by Shinohara and Yagi in 2022. Introducing a measure of privacy for the encoder, we investigate the following two problems: The first problem is the first-order rate analysis among the coding rate, utility, privacy for the decoder, and privacy for the encoder, in which utility is measured by the expected distortion or the excess-distortion probability. The second task is establishing the strong converse theorem for utility–privacy trade-offs, in which utility is measured by the excess-distortion probability. These results may lead to a more refined analysis such as the second-order rate analysis.
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spelling pubmed-102973842023-06-28 Utility–Privacy Trade-Offs with Limited Leakage for Encoder Shinohara, Naruki Yagi, Hideki Entropy (Basel) Article The utilization of databases such as IoT has progressed, and understanding how to protect the privacy of data is an important issue. As pioneering work, in 1983, Yamamoto assumed the source (database), which consists of public information and private information, and found theoretical limits (first-order rate analysis) among the coding rate, utility and privacy for the decoder in two special cases. In this paper, we consider a more general case based on the work by Shinohara and Yagi in 2022. Introducing a measure of privacy for the encoder, we investigate the following two problems: The first problem is the first-order rate analysis among the coding rate, utility, privacy for the decoder, and privacy for the encoder, in which utility is measured by the expected distortion or the excess-distortion probability. The second task is establishing the strong converse theorem for utility–privacy trade-offs, in which utility is measured by the excess-distortion probability. These results may lead to a more refined analysis such as the second-order rate analysis. MDPI 2023-06-11 /pmc/articles/PMC10297384/ /pubmed/37372265 http://dx.doi.org/10.3390/e25060921 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Shinohara, Naruki
Yagi, Hideki
Utility–Privacy Trade-Offs with Limited Leakage for Encoder
title Utility–Privacy Trade-Offs with Limited Leakage for Encoder
title_full Utility–Privacy Trade-Offs with Limited Leakage for Encoder
title_fullStr Utility–Privacy Trade-Offs with Limited Leakage for Encoder
title_full_unstemmed Utility–Privacy Trade-Offs with Limited Leakage for Encoder
title_short Utility–Privacy Trade-Offs with Limited Leakage for Encoder
title_sort utility–privacy trade-offs with limited leakage for encoder
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10297384/
https://www.ncbi.nlm.nih.gov/pubmed/37372265
http://dx.doi.org/10.3390/e25060921
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