TARU PUBLICATIONS
Journal of Discrete Mathematical Sciences and Cryptography cover
Open Access ·Peer-reviewed·ISSN (Online): 2169-0065·ISSN (Print): 0972-0529

Monthly Journal: Publishes theoretical and applied research in all areas of Discrete Mathematical Sciences, Cryptography, Combinatorics, Elliptic Curves and Information Security.

Issues up to 2022 co-published with and available at:Taylor & Francis Online
submissions@tarupublications.com
Open Access Research Article

Privacy preserving protocols for encrypted data comparison in semi-honest cloud environment

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pp. 1825–1834Vol. 28Issue 5-AAugust 2025DOI: 10.47974/JDMSC-2182 Crossmark XML
Received:
05 Nov 2024
Published Online:
30 Aug 2025
Article type:
Research Article
Language:
EN
Article no.:
JDMSC-2182
Pages:
1825–1834

Abstract

Currently, with third-party cloud providers handling data mining tasks while securely processing sensitive data has become critical. These providers may exploit intermediate data during computation, posing privacy risks. In privacy-preserving classification, we address a secure comparison problem where inputs a and b are encrypted, ensuring no plaintext is exposed to the cloud. Our protocol, designed for a semi-honest model, allows only the end user to learn whether a > b, keeping both inputs hidden from cloud parties. While initially targeting single comparisons, our protocol scales to multiple encrypted inputs to identify the maximum value securely. It thus serves as a foundational tool for secure data processing. Additionally, we introduce a second protocol utilizing homomorphic encryption’s additive property to compare encrypted values efficiently, reducing both computational and communication overhead. Both protocols avoid circuit-based methods and operate in a fixed number of rounds, enhancing performance.

Keywords

Subject Classifications

Primary 93A30Secondary 49K15

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