Efficient Private Information Retrieval Scheme with Dynamic Database Article Swipe
Xin Li
,
Wenju Xu
,
Dianhua Tang
,
Yunfei Cao
,
Jing Zhang
,
Wei Zhao
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/electronics14173441
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/electronics14173441
Private information retrieval (PIR) is a typical application scenario of encrypted computing, which allows users to retrieve data from a database by providing only an encrypted index. In an academic research scenario, multiple parties may entrust their data to a third party and require collaborative retrieval. However, due to competitive relationships and mutual distrust between these parties, they do not share public–private keys, making single-key mechanisms inadequate for meeting actual privacy requirements. In this case, based on the multi-key fully homomorphic encryption (MKFHE) algorithm, we construct an efficient PIR scheme with an access permission verification mechanism and dynamic database. Specifically, we design an MKFHE algorithm to protect multi-user privacy information. The vector–matrix multiplication optimization algorithm is adopted to improve computational efficiency, the expand algorithm is used to reduce user communication traffic, and homomorphic multiplication with ciphertext chunking is used to avoid excessive noise caused by direct ciphertext multiplication. Experiments based on the SEAL library show that by transferring part of the computational pressure to the offline stage, the online query response efficiency of our scheme is improved by about 7.69%, and the online computational efficiency of vector–matrix multiplication is improved by about 19.7%.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/electronics14173441
- https://www.mdpi.com/2079-9292/14/17/3441/pdf?version=1756431377
- OA Status
- gold
- Cited By
- 1
- References
- 19
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4413832561
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Raw OpenAlex JSON
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- DOI
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https://doi.org/10.3390/electronics14173441Digital Object Identifier
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Efficient Private Information Retrieval Scheme with Dynamic DatabaseWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-08-29Full publication date if available
- Authors
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Xin Li, Wenju Xu, Dianhua Tang, Yunfei Cao, Jing Zhang, Wei ZhaoList of authors in order
- Landing page
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https://doi.org/10.3390/electronics14173441Publisher landing page
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https://www.mdpi.com/2079-9292/14/17/3441/pdf?version=1756431377Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2079-9292/14/17/3441/pdf?version=1756431377Direct OA link when available
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Scheme (mathematics), Computer science, Database, Information retrieval, Data mining, Mathematics, Mathematical analysisTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.(PIR) | 3 |
| abstract_inverted_index.MKFHE | 103 |
| abstract_inverted_index.about | 178, 191 |
| abstract_inverted_index.avoid | 140 |
| abstract_inverted_index.based | 75, 149 |
| abstract_inverted_index.case, | 74 |
| abstract_inverted_index.fully | 79 |
| abstract_inverted_index.keys, | 62 |
| abstract_inverted_index.noise | 142 |
| abstract_inverted_index.party | 41 |
| abstract_inverted_index.query | 169 |
| abstract_inverted_index.share | 60 |
| abstract_inverted_index.their | 36 |
| abstract_inverted_index.these | 55 |
| abstract_inverted_index.third | 40 |
| abstract_inverted_index.users | 14 |
| abstract_inverted_index.which | 12 |
| abstract_inverted_index.19.7%. | 192 |
| abstract_inverted_index.7.69%, | 179 |
| abstract_inverted_index.access | 92 |
| abstract_inverted_index.actual | 69 |
| abstract_inverted_index.allows | 13 |
| abstract_inverted_index.caused | 143 |
| abstract_inverted_index.design | 101 |
| abstract_inverted_index.direct | 145 |
| abstract_inverted_index.expand | 122 |
| abstract_inverted_index.index. | 26 |
| abstract_inverted_index.making | 63 |
| abstract_inverted_index.mutual | 52 |
| abstract_inverted_index.online | 168, 182 |
| abstract_inverted_index.reduce | 127 |
| abstract_inverted_index.scheme | 89, 174 |
| abstract_inverted_index.stage, | 166 |
| abstract_inverted_index.(MKFHE) | 82 |
| abstract_inverted_index.Private | 0 |
| abstract_inverted_index.adopted | 116 |
| abstract_inverted_index.between | 54 |
| abstract_inverted_index.dynamic | 97 |
| abstract_inverted_index.entrust | 35 |
| abstract_inverted_index.improve | 118 |
| abstract_inverted_index.library | 153 |
| abstract_inverted_index.meeting | 68 |
| abstract_inverted_index.offline | 165 |
| abstract_inverted_index.parties | 33 |
| abstract_inverted_index.privacy | 70, 108 |
| abstract_inverted_index.protect | 106 |
| abstract_inverted_index.require | 43 |
| abstract_inverted_index.typical | 6 |
| abstract_inverted_index.However, | 46 |
| abstract_inverted_index.academic | 29 |
| abstract_inverted_index.chunking | 136 |
| abstract_inverted_index.database | 20 |
| abstract_inverted_index.distrust | 53 |
| abstract_inverted_index.improved | 176, 189 |
| abstract_inverted_index.multiple | 32 |
| abstract_inverted_index.parties, | 56 |
| abstract_inverted_index.pressure | 162 |
| abstract_inverted_index.research | 30 |
| abstract_inverted_index.response | 170 |
| abstract_inverted_index.retrieve | 16 |
| abstract_inverted_index.scenario | 8 |
| abstract_inverted_index.traffic, | 130 |
| abstract_inverted_index.algorithm | 104, 114, 123 |
| abstract_inverted_index.construct | 85 |
| abstract_inverted_index.database. | 98 |
| abstract_inverted_index.efficient | 87 |
| abstract_inverted_index.encrypted | 10, 25 |
| abstract_inverted_index.excessive | 141 |
| abstract_inverted_index.mechanism | 95 |
| abstract_inverted_index.multi-key | 78 |
| abstract_inverted_index.providing | 22 |
| abstract_inverted_index.retrieval | 2 |
| abstract_inverted_index.scenario, | 31 |
| abstract_inverted_index.algorithm, | 83 |
| abstract_inverted_index.ciphertext | 135, 146 |
| abstract_inverted_index.computing, | 11 |
| abstract_inverted_index.efficiency | 171, 184 |
| abstract_inverted_index.encryption | 81 |
| abstract_inverted_index.inadequate | 66 |
| abstract_inverted_index.mechanisms | 65 |
| abstract_inverted_index.multi-user | 107 |
| abstract_inverted_index.permission | 93 |
| abstract_inverted_index.retrieval. | 45 |
| abstract_inverted_index.single-key | 64 |
| abstract_inverted_index.Experiments | 148 |
| abstract_inverted_index.application | 7 |
| abstract_inverted_index.competitive | 49 |
| abstract_inverted_index.efficiency, | 120 |
| abstract_inverted_index.homomorphic | 80, 132 |
| abstract_inverted_index.information | 1 |
| abstract_inverted_index.information. | 109 |
| abstract_inverted_index.optimization | 113 |
| abstract_inverted_index.transferring | 157 |
| abstract_inverted_index.verification | 94 |
| abstract_inverted_index.Specifically, | 99 |
| abstract_inverted_index.collaborative | 44 |
| abstract_inverted_index.communication | 129 |
| abstract_inverted_index.computational | 119, 161, 183 |
| abstract_inverted_index.relationships | 50 |
| abstract_inverted_index.requirements. | 71 |
| abstract_inverted_index.multiplication | 112, 133, 187 |
| abstract_inverted_index.multiplication. | 147 |
| abstract_inverted_index.vector–matrix | 111, 186 |
| abstract_inverted_index.public–private | 61 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.9547528 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |