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Heal the Privacy: Functional Encryption and Privacy-Preserving Analytics

2022/05/06 by Alexandros Bakas, Bakas, Alexandros, Antonis Michalas +1
Computer Science · #Chaos-based Image/Signal Encryption #Cryptography and Data Security #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Privacy-Preserving Technologies in Data

paper · pdf · doi:10.48550/arxiv.2205.03083

openalex publication_date 2022/05/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/03

Abstract

Secure cloud storage is an issue of paramount importance that both businesses and end-users should take into consideration before moving their data to, potentially, untrusted clouds. Migrating data to the cloud raises multiple privacy issues, as they are completely controlled by a cloud provider. Hence, an untrusted cloud provider can potentially breach users; privacy and gain access to sensitive information. The problem becomes even more pronounced when the could provider is required to store a statistical database and periodically publish analytics. In this work, we first present a detailed example showing that the use of cryptography is not enough to ensure the privacy of individuals. Then, we design a hybrid protocol based on Functional Encryption and Differential Privacy that allows the computations of statistics in a privacy-preserving way.

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