Hash-Comb: A Hierarchical Distance-Preserving Multi-Hash Data Representation for Collaborative Analytics

Hash-Comb: A Hierarchical Distance-Preserving Multi-Hash Data Representation for Collaborative Analytics

Data privacy regulations like the EU GDPR allow the use of hashing techniques to anonymize data that may contain personal information. However, cryptographic hashing is well-known to destroy any possibility of performing analytics. Homomorphic crypto-systems allow computing analytics over encrypted...

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Bibliographic Details
Main Authors: Abdelrahman Almahmoud, Ernesto Damiani, Hadi Otrok
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Data privacy
distance-preserving hashing
big data
homomorphic encryption
hashing
quantization kit
Online Access:https://ieeexplore.ieee.org/document/9733341/

Internet

https://ieeexplore.ieee.org/document/9733341/

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