This standard specifies the architecture and technical requirements of differential privacy for personal information protection in Artificial Intelligence model training. Differential privacy provides a framework for ensuring the privacy of individuals in datasets by allowing data to be analyzed without revealing sensitive information about any specific individual. The requirements consist of data security, algorithm security and scenario-based system security of differential privacy technology used in model training process. This standard also provides classification methodologies of differential privacy technology.
- Standard Committee
- C/AISC - Artificial Intelligence Standards Committee
- Status
- Active PAR
- PAR Approval
- 2023-09-21
Working Group Details
- Society
- IEEE Computer Society
- Standard Committee
- C/AISC - Artificial Intelligence Standards Committee
- Working Group
-
PETS - Privacy-Enhancing Technology Security Working Group
- IEEE Program Manager
- Christy Bahn
Contact Christy Bahn - Working Group Chair
- Tianning Huangtn
Other Activities From This Working Group
Current projects that have been authorized by the IEEE SA Standards Board to develop a standard.
No Active Projects
Standards approved by the IEEE SA Standards Board that are within the 10-year lifecycle.
No Active Standards
These standards have been replaced with a revised version of the standard, or by a compilation of the original active standard and all its existing amendments, corrigenda, and errata.
No Superseded Standards
These standards have been removed from active status through a ballot where the standard is made inactive as a consensus decision of a balloting group.
No Inactive-Withdrawn Standards
These standards are removed from active status through an administrative process for standards that have not undergone a revision process within 10 years.
No Inactive-Reserved Standards