Natural differential privacy—a perspective on protection guarantees
Name
peerj-cs-1576.pdf
Size
8.81 MB
Format
Adobe PDF
Checksum (MD5)
690a1d818909601078711ebae09e05ac
Author(s)
Altman, Micah
Cohen, Aloni
Date Issued
September 28, 2023
Journal
PeerJ Computer Science
Publisher
PeerJ
Citation
Altman M, Cohen A. 2023. Natural differential privacy—a perspective on protection guarantees. PeerJ Computer Science 9:e1576.
Version
Final published version
Abstract
We introduce “Natural” differential privacy (NDP)—which utilizes features of existing hardware architecture to implement differentially private computations. We show that NDP both guarantees strong bounds on privacy loss and constitutes a practical exception to no-free-lunch theorems on privacy. We describe how NDP can be efficiently implemented and how it aligns with recognized privacy principles and frameworks. We discuss the importance of formal protection guarantees and the relationship between formal and substantive protections.
Subjects
General Computer Science
MIT Department
Center for Research on Equitable and Open Scholarship
Massachusetts Institute of Technology. Libraries
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.7717/peerj-cs.1576
