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.
- Sponsor Committee
- C/AISC - Artificial Intelligence Standards Committee
- Status
- Active PAR
- PAR Approval
- 2023-09-21
Working Group Details
- Society
- IEEE Computer Society
Learn More About IEEE Computer Society - Sponsor Committee
- C/AISC - Artificial Intelligence Standards Committee
- Working Group
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PETS - Privacy-Enhancing Technology Security Working Group
Learn More About PETS - Privacy-Enhancing Technology Security Working Group - IEEE Program Manager
- Christy Bahn
Contact Christy Bahn - Working Group Chair
- Tianning Huangtn
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