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A Framework for Privacy-Preserving Multiparty Computation with Homomorphic Encryption and Zero-Knowledge Proofs

Janak Dhokrat, Namita Pulgam, Tabassum Maktum, Vanita Mane

2024Informatica14 citationsDOIOpen Access PDF

Abstract

In digital landscape of today’s ongoing world, the imperative for enhanced security in cloud-based data processing is paramount. This paper introduces an innovative framework that seamlessly integrates Homomorphic Encryption and Zero-Knowledge Proofs (ZKPs) to bolster data privacy and confidentiality. This paper explores the technical intricacies, real-world applications, and potential implications of this fusion framework. Homomorphic Encryption empowers computations on encrypted data without compromising privacy, while Zero-Knowledge Proofs offer a mechanism to verify computations without exposing sensitive details. The effectiveness and adaptability of the proposed framework is demonstrated through meticulous analysis and practical deployment in safeguarding cloud-based data processing. The proposed framework marks a significant stride towards creating an environment where data security is unequivocally prioritized.

Topics & Concepts

Homomorphic encryptionZero-knowledge proofMathematical proofComputer scienceBlockchainComputationEncryptionTheoretical computer scienceComputer securityCryptographyMathematicsAlgorithmGeometryCryptography and Data SecurityPrivacy-Preserving Technologies in DataComplexity and Algorithms in Graphs
A Framework for Privacy-Preserving Multiparty Computation with Homomorphic Encryption and Zero-Knowledge Proofs | Litcius