multi-party computation

AntTech

Apr 10, 2023 · Information Security

First Batch of Multi-Party Secure Computation FinTech Products Certified by Beijing National FinTech Certification Center

Beijing's National FinTech Certification Center announced that five fintech products, including AntChain MOSS and Ant Wind Tunnel multi‑party secure computation platforms, have passed the country's first national certification for multi‑party secure computation, highlighting the technology's growing importance in finance and data security.

Ant GroupChinaFinTech

0 likes · 6 min read

First Batch of Multi-Party Secure Computation FinTech Products Certified by Beijing National FinTech Certification Center

DataFunSummit

Feb 15, 2023 · Information Security

Challenges and Trends in Privacy Computing: Insights from Alibaba Cloud Datatrust Architect Liang Aiping

The interview with Alibaba Cloud Datatrust chief architect Liang Aiping examines the early-stage adoption of privacy computing, highlighting low technical challenges in data sources, the gap between theory and engineering in algorithms, complex system management for interoperability, and key product considerations such as security, performance, cost, and deployment.

algorithm evaluationdata securitymulti-party computation

0 likes · 13 min read

Challenges and Trends in Privacy Computing: Insights from Alibaba Cloud Datatrust Architect Liang Aiping

DataFunSummit

Dec 27, 2022 · Blockchain

Financial Technology Testing Facilitates Secure Data Sharing in Finance

The article explains how emerging collaboration models, privacy‑computing and blockchain technologies, together with evolving regulations and industry standards, enable secure and compliant financial data sharing, describing the technical foundations, evaluation criteria, and practical testing practices that support trustworthy FinTech products.

Federated LearningFinTech standardsblockchain

0 likes · 22 min read

Financial Technology Testing Facilitates Secure Data Sharing in Finance

DataFunSummit

Dec 26, 2022 · Information Security

Privacy Computing in Digital Government: Background, Technical Roadmap, Case Studies, Challenges, and Recommendations

This article introduces the background, technical roadmap, real-world cases, implementation challenges, and suggested approaches for privacy computing in digital government, highlighting how secure multi‑party computation, federated learning, and trusted execution environments can enable safe data sharing.

Federated Learningdata securitydigital government

0 likes · 18 min read

Privacy Computing in Digital Government: Background, Technical Roadmap, Case Studies, Challenges, and Recommendations

DataFunSummit

Jun 9, 2022 · Information Security

Data Usage Control and Multi‑Party Secure Computation: Policy Background, Technical Implementation, and Future Outlook

This article examines data usage control and multi‑party secure computation, covering relevant Chinese policies, the technical mechanisms such as computing contracts and blockchain integration, and future directions for regulatory digitization and standardization, while emphasizing trust, auditability, and privacy preservation.

blockchaindata securitymulti-party computation

0 likes · 17 min read

Data Usage Control and Multi‑Party Secure Computation: Policy Background, Technical Implementation, and Future Outlook

AntTech

Jun 17, 2020 · Artificial Intelligence

Shared Intelligence: Combining Trusted Execution Environments and Multi‑Party Computation for Privacy‑Preserving Machine Learning at Ant Group

This article presents Ant Group's shared‑intelligence solution that integrates Trusted Execution Environments (TEE) and Multi‑Party Computation (MPC) to enable privacy‑preserving data sharing and large‑scale machine‑learning across untrusted parties, discusses industry progress, technical evolution, practical deployments, and future challenges.

Ant GroupData Sharingmulti-party computation

0 likes · 17 min read

Shared Intelligence: Combining Trusted Execution Environments and Multi‑Party Computation for Privacy‑Preserving Machine Learning at Ant Group

AntTech

Mar 4, 2020 · Artificial Intelligence

Shared Intelligence vs. Federated Learning: Ant Group’s Privacy‑Preserving Machine Learning Solutions for Finance

The article explains how Ant Group tackles the privacy‑usability trade‑off in AI by combining Trusted Execution Environments and Multi‑Party Computation into a “shared intelligence” framework, contrasting it with federated learning, detailing technical architectures, training workflows, and its impact on financial data sharing.

Data SharingFederated Learningfinancial technology

0 likes · 14 min read

Shared Intelligence vs. Federated Learning: Ant Group’s Privacy‑Preserving Machine Learning Solutions for Finance

AntTech

Aug 17, 2019 · Artificial Intelligence

Shared Machine Learning: Tackling Data Islands with Trusted Execution Environments and Multi‑Party Computation

The article explains how data islands and privacy concerns hinder AI development and describes Ant Financial's shared machine learning approach, which combines Trusted Execution Environments (TEE) and Multi‑Party Computation (MPC) to enable secure, privacy‑preserving data sharing and collaborative model training across organizations.

AIData Sharingant financial

0 likes · 15 min read

Shared Machine Learning: Tackling Data Islands with Trusted Execution Environments and Multi‑Party Computation