This standard defines an interworking framework for privacy-preserving computation. This framework consists of interworking network requirements, technical flows, functional requirements, and security requirements.
The purpose of this standard is to define mechanisms which enable interoperability between different privacy-preserving computation platforms, including trusted execution environment, federated machine learning, and secure multiparty computation to facilitate data circulation and data value exchange. Privacy-preserving computation can be used to perform data analysis and computation without disclosing the original data from data providers.
New IEEE Standard – Active – Draft. This standard specifies a basic architecture of privacy-preserving computation interworking framework, and defines the specification of node interworking, resource interworking and algorithm component interworking.
The purpose of this standard is to define mechanisms which enable interoperability between different privacy-preserving computation platforms, including trusted execution environment, federated machine learning, and secure multiparty computation to facilitate data circulation and data value exchange. Privacy-preserving computation can be used to perform data analysis and computation without disclosing the original data from data providers.
New IEEE Standard – Active – Draft. This standard specifies a basic architecture of privacy-preserving computation interworking framework, and defines the specification of node interworking, resource interworking and algorithm component interworking.
