Achieving privacy-preserving sensitive attributes for large universe based on private set intersection

DOI10.1016/J.INS.2021.09.034OpenAlexW3201614101MaRDI QIDQ6178358

No author found.

Publication date: 18 January 2024

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2021.09.034

zbMATH Keywords

private set intersectionlarge universehiding policy fullytag vectors

Mathematics Subject Classification ID

Computer science (68-XX) Information and communication theory, circuits (94-XX)

Cites Work

• The internet of things: a survey
• Efficient attribute-based encryption with attribute revocation for assured data deletion
• Privately outsourcing exponentiation to a single server: cryptanalysis and optimal constructions
• Predicate encryption supporting disjunctions, polynomial equations, and inner products
• A privacy-preserving cryptosystem for IoT E-healthcare
• Fully Secure Cipertext-Policy Hiding CP-ABE
• Ciphertext-Policy Attribute-Based Encryption: An Expressive, Efficient, and Provably Secure Realization
• Fully Secure Hidden Ciphertext-Policy Attribute-Based Proxy Re-encryption
• Privacy-Aware Attribute-Based Encryption with User Accountability
• Fully Secure Functional Encryption: Attribute-Based Encryption and (Hierarchical) Inner Product Encryption
• Conjunctive, Subset, and Range Queries on Encrypted Data
• Fuzzy Identity-Based Encryption
• Predicate Encryption Supporting Disjunctions, Polynomial Equations, and Inner Products

This page was built for publication: Achieving privacy-preserving sensitive attributes for large universe based on private set intersection