Privacy Computing System is a data privacy computing system based on core technologies, including federated learning, secure multi-party computation, trusted execution environment, and blockchain. It provides privacy protection for data exchange and data sharing, through protection of user data from leakage and escort of data element circulation.
Cross-chain Big Data Platform is a data circulation service platform based on core technologies, such as trusted blockchain and big data. It boosts digital economic progress through full-chain data circulation services, such as data release, data sharing, data query, and data transaction, as well as through mining of data value.
Privacy Computing System secures “available yet invisible” data, based on a series of technologies, such as federated learning, secure multi-party computation, trusted blockchain, and more.
Distributed Machine Learning Paradigm. Solves the problem of data silos.
No need for data sharing among parties. No data owner node revealed in data plaintext.
Protects data privacy; secures “available yet invisible” data.
Data computing based on cryptographic protection.
Calculation without revealing any local raw data.
No information other than calculation results can be obtained by either party.
Extracts data value without revealing raw data.
Blockchain System Behavior Storage Certification. Tamper-proof at Bitcoin ledger level.
All records are saved incrementally; All changes are recorded and can be traced and verified.
Provides unique heterogeneous consensus;strengthens consensus efficiency and blockchain security.
100,000 TPS (Storage Transactions Per Second). Enables storage efficiency at database level.
Blockchain-based data sharing and publishing; ensures data authenticity.
Automated on-chain data release and update; enhanced data sharing efficiency.
Visualized data flow supervision.
Offers users innovative technical solutions for data circulation, data sharing, and data transaction, through Privacy Computing System and Cross-chain Big Data Platform; satisfies needs of various industries for data circulation; speeds up digital economic construction through mining of data value.
Protects privacy through various technologies, such as federated learning, multi-party secure computation, and TEE; tailored to meet needs in different scenarios.
Visualized operation for all functions; easy for data circulation.
Full-chain solutions for data circulation, including privacy computing, data release, data query, and data transaction.
No tampering allowed during whole privacy computing process
Cutting-edge research capabilities in privacy computing. Realizes whole-process independent research and development for privacy computing products, from underlying systems, cryptographic algorithms, to machine learning algorithms; realizes autonomous control for entire Privacy Computing System.
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Privacy Computing System is a data privacy computing system based on core technologies, including federated learning, secure multi-party computation, trusted execution environment, and blockchain. It provides privacy protection for data exchange and data sharing, through protection of user data from leakage and escort of data element circulation.
Cross-chain Big Data Platform is a data circulation service platform based on core technologies, such as trusted blockchain and big data. It boosts digital economic progress through full-chain data circulation services, such as data release, data sharing, data query, and data transaction, as well as through mining of data value.
Privacy Computing System secures “available yet invisible” data, based on a series of technologies, such as federated learning, secure multi-party computation, trusted blockchain, and more.
Data computing based on cryptographic protection.
Calculation without revealing any local raw data.
No information other than calculation results can be obtained by either party.
Extracts data value without revealing raw data.
Blockchain-based data sharing and publishing; ensures data authenticity.
Automated on-chain data release and update; enhanced data sharing efficiency.
Visualized data flow supervision.
Distributed Machine Learning Paradigm. Solves the problem of data silos.
No need for data sharing among parties. No data owner node revealed in data plaintext.
Protects data privacy; secures “available yet invisible” data.
Blockchain System Behavior Storage Certification. Tamper-proof at Bitcoin ledger level.
All records are saved incrementally. All changes can be recorded, traced, and verified.
Provides unique heterogeneous consensus;strengthens consensus efficiency and blockchain security.
100,000 TPS (Storage Transactions Per Second). Enables storage efficiency at database level.
Offers users innovative technical solutions for data circulation, data sharing, and data transaction, through Privacy Computing System and Cross-chain Big Data Platform; satisfies needs of various industries for data circulation; speeds up digital economic construction through mining of data value.
Protects privacy through various technologies, such as federated learning, multi-party secure computation, and TEE; tailored to meet needs in different scenarios.
Full-chain solutions for data circulation, including privacy computing, data release, data query, and data transaction.
Cutting-edge research capabilities in privacy computing. Realizes whole-process independent research and development for privacy computing products, from underlying systems, cryptographic algorithms, to machine learning algorithms; realizes autonomous control for entire Privacy Computing System.
Visualized operation for all functions; easy for data circulation.
No tampering allowed during whole privacy computing process;traceable on-chain transactions during whole data circulation process.