Study of Homomorphic Encoding Scheme

This paper provides a study of the Homomorphic Encryption (HE) scheme, which enables computations to be performed directly on encrypted data without prior decryption, thereby addressing crucial data privacy and security concerns, particularly in cloud computing environments. The work classifies HE into three categories: Partially Homomorphic Encryption (PHE), Somewhat Homomorphic Encryption (SWHE), and Fully Homomorphic Encryption (FHE), detailing the operational capabilities and constraints of each. It reviews the theoretical and historical advancements in the field, including Gentry's pioneering work on bootstrapping. Furthermore, the paper explores advanced applications of HE in privacy-preserving scenarios such as Encrypted Health Monitoring Systems, GPS Trackers, Wearable Health Trackers, and Home Security Systems. The conclusion emphasizes that while HE is a promising approach for robust data protection, the feasibility and performance of FHE still require significant improvement across all platforms.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-15
DOI
https://doi.org/10.5281/zenodo.17356131
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
0.00
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article

Study of Homomorphic Encoding Scheme

Zenodo (CERN European Organization for Nuclear Research)
Cryptography and Data Security
article

Study of Homomorphic Encoding Scheme

article en

Abstract

This paper provides a study of the Homomorphic Encryption (HE) scheme, which enables computations to be performed directly on encrypted data without prior decryption, thereby addressing crucial data privacy and security concerns, particularly in cloud computing environments. The work classifies HE into three categories: Partially Homomorphic Encryption (PHE), Somewhat Homomorphic Encryption (SWHE), and Fully Homomorphic Encryption (FHE), detailing the operational capabilities and constraints of each. It reviews the theoretical and historical advancements in the field, including Gentry's pioneering work on bootstrapping. Furthermore, the paper explores advanced applications of HE in privacy-preserving scenarios such as Encrypted Health Monitoring Systems, GPS Trackers, Wearable Health Trackers, and Home Security Systems. The conclusion emphasizes that while HE is a promising approach for robust data protection, the feasibility and performance of FHE still require significant improvement across all platforms.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 24%
Cryptography and Data Security
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