SOCI: A Toolkit for Secure Outsourced Computation on Integers
Secure outsourced computation is a key technique for protecting data security and privacy in the cloud. Although fully homomorphic encryption (FHE) enables computations over encrypted data, it suffers from high computation costs in order to support an unlimited number of arithmetic operations. Recen...
Saved in:
Main Authors: | , , , , , |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2022
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/7587 https://ink.library.smu.edu.sg/context/sis_research/article/8590/viewcontent/SOCI.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Summary: | Secure outsourced computation is a key technique for protecting data security and privacy in the cloud. Although fully homomorphic encryption (FHE) enables computations over encrypted data, it suffers from high computation costs in order to support an unlimited number of arithmetic operations. Recently, secure computations based on interactions of multiple computation servers and partially homomorphic encryption (PHE) were proposed in the literature, which enable an unbound number of addition and multiplication operations on encrypted data more efficiently than FHE and do not add any noise to encrypted data; however, these existing solutions are either limited in functionalities (e.g., computation on natural numbers only) or leak information of the underlying data. To tackle these shortcomings, this paper proposes Secure Outsourced Computation on Integers (SOCI) based on PHE and a twin-server architecture. Compared with the existing solutions, SOCI supports computations on encrypted integers (vs. natural numbers) and greatly improves the security and correctness of the computations. Results of theoretical analysis and experimental evaluation show that SOCI outperforms existing solutions in computation and communication efficiencies. |
---|