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

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.

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Publication Details

Journal
Informatica
Published
2024-11-27
DOI
https://doi.org/10.31449/inf.v48i21.6562
Citations
12
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
4.17
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article

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

Tabassum Maktum, Vanita Mane, Namita Pulgam, Janak Dhokrat
12 citations
Informatica
Cryptography and Data Security
4.17
article

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

Tabassum Maktum, Vanita Mane, Namita Pulgam, Janak Dhokrat
article en
12 citations

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.

InformaticaVol. 48(21)
D.Y. Patil University (IN)
Openalex Percentile: Top 5%
Cryptography and Data Security
4.17
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A Framework for Privacy-Preserving Multiparty Computation with Homomorphic Encryption and Zero-Knowledge Proofs — Tabassum Maktum, Vanita Mane, et al. · Informatica (2024) | TGRS Research Map | TGRS