Fuzzy Labeled Private Set Intersection Protocol

Fuzzy labeled private set intersection(FLPSI) is a variant of PSI where the elements in the sender’s and receiver’s sets are not the same but rather have some similarities.Each element in the sender’s set is associated with a label,and the receiver only receives the labels of the matched elements and without revealing other information.Most existing FLPSI protocols use Hamming distance to determine the degree of matching between binary vectors.These protocols are built based on expensive public key ciphers,which requiring high computation overhead and resulting in slow running time.This paper proposes an efficient FLPSI protocol based on symmetric cryptography.It proves the security of the PSI protocol in the semi-honest model,ensuring that participants cannot obtain additional data.Compared to the existing schemes,the protocol reduces the overall communication complexity and the computational complexity of the sender from O(<i>n</i><sup>2</sup>) to O(<i>n)</i>.Through experimental simulation,in balanced scenarios,the proposed protocol is 3~10x faster than the existing FLPSI protocol,and the communication is reduced by 89% to 95%.In unbalanced scenarios,the proposed protocol is 7~10x faster than the existing FLPSI protocol,and it also exhibits ob-vious advantages over similar fuzzy matching protocols.In addition,the application of FLPSI protocol in face recognition under privacy protection conditions is designed,which can meet the requirements of different scenarios by adjusting parameters.

Institutions

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-12-01
DOI
https://doi.org/10.11896/jsjkx.231000131
Primary Topic
Research on Leishmaniasis Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fuzzy Labeled Private Set Intersection Protocol

SHILAP Revista de lepidopterología
Research on Leishmaniasis Studies
article

Fuzzy Labeled Private Set Intersection Protocol

article en

Abstract

Fuzzy labeled private set intersection(FLPSI) is a variant of PSI where the elements in the sender’s and receiver’s sets are not the same but rather have some similarities.Each element in the sender’s set is associated with a label,and the receiver only receives the labels of the matched elements and without revealing other information.Most existing FLPSI protocols use Hamming distance to determine the degree of matching between binary vectors.These protocols are built based on expensive public key ciphers,which requiring high computation overhead and resulting in slow running time.This paper proposes an efficient FLPSI protocol based on symmetric cryptography.It proves the security of the PSI protocol in the semi-honest model,ensuring that participants cannot obtain additional data.Compared to the existing schemes,the protocol reduces the overall communication complexity and the computational complexity of the sender from O(<i>n</i><sup>2</sup>) to O(<i>n)</i>.Through experimental simulation,in balanced scenarios,the proposed protocol is 3~10x faster than the existing FLPSI protocol,and the communication is reduced by 89% to 95%.In unbalanced scenarios,the proposed protocol is 7~10x faster than the existing FLPSI protocol,and it also exhibits ob-vious advantages over similar fuzzy matching protocols.In addition,the application of FLPSI protocol in face recognition under privacy protection conditions is designed,which can meet the requirements of different scenarios by adjusting parameters.

SHILAP Revista de lepidopterología
Shanghai Ocean University (CN), Shanghai Maritime University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 38%
Research on Leishmaniasis Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.