MPC | BestHub

AntTech

Oct 31, 2024 · Information Security

Coral: A Maliciously Secure Computation Framework for Packed and Mixed Circuits

Ant Group’s cryptography lab introduced Coral, a new maliciously secure multi‑party computation framework that leverages a reverse multiplication‑friendly embedding (RMFE) to efficiently handle packed and mixed circuits, enhancing security from semi‑honest to fully malicious models and delivering practical performance improvements.

Ant GroupMPCMalicious Security

0 likes · 4 min read

Coral: A Maliciously Secure Computation Framework for Packed and Mixed Circuits

AntTech

Jul 7, 2024 · Information Security

2024 WAIC Forum on Privacy Computing: Enabling Trusted Data Sharing for Large Models

The 2024 WAIC Privacy Computing Forum gathered leading experts from academia and industry to discuss how encryption, anonymization, and secure multi‑party computation can protect data privacy while enabling large‑model training and inference, highlighting technical challenges, standards, and emerging solutions across AI, big data, and information security domains.

AIData SecurityMPC

0 likes · 15 min read

2024 WAIC Forum on Privacy Computing: Enabling Trusted Data Sharing for Large Models

AntTech

Dec 22, 2023 · Information Security

2023 Security and Trustworthy Computing Research Summary – 14 Papers Accepted at Top International Conferences

In late 2023, Ant Group and academic partners reported fourteen security‑focused research papers accepted at top venues such as USENIX Security, ACM CCS, and USENIX ATC, covering privacy‑preserving computation, secure two‑party GBDT training, macOS kernel fuzzing, privacy‑preserving ML frameworks, Rust OOM handling, and more.

MPCcryptographyprivacy

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2023 Security and Trustworthy Computing Research Summary – 14 Papers Accepted at Top International Conferences

AntTech

Dec 12, 2023 · Information Security

Privacy Computing Case Study: Multi‑Party Secure Computation for Financial Risk Control by Jiangsu Bank and Ningbo Bank

This article presents a detailed case study of how Jiangsu Bank and Ningbo Bank leveraged Ant Group’s multi‑party secure computation platform and the “YinYu” privacy‑computing framework to build joint risk‑control models, enhancing data sharing, security, and approval rates for inclusive finance.

Data SecurityInclusive FinanceMPC

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Privacy Computing Case Study: Multi‑Party Secure Computation for Financial Risk Control by Jiangsu Bank and Ningbo Bank

AntTech

Sep 2, 2023 · Information Security

Innovative Cryptographic Technologies and Applications Forum – Session Summaries and Speaker Information

The announcement details a September 7 forum hosted by the China Cryptology Society, featuring eight technical talks on cutting‑edge cryptographic and data‑security technologies—including hardware security, secure GPT inference, volume‑hiding encrypted multi‑maps, end‑to‑same‑end encryption, fully homomorphic encryption databases, dishonest‑majority MPC, active privacy computing, and the Bicoptor protocol—along with speaker biographies and abstracts.

Data SecurityMPCSecure Computation

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Innovative Cryptographic Technologies and Applications Forum – Session Summaries and Speaker Information

DataFunSummit

Aug 27, 2023 · Artificial Intelligence

Privacy-Preserving Gradient Boosting Decision Trees via Multi-Party Computation and the Squirrel Framework

This article introduces a privacy-preserving gradient boosting decision tree (GBDT) solution built on multi‑party computation, detailing its background, training steps, the MPC tools used, and the Squirrel framework’s workflow, while discussing performance challenges and experimental results demonstrating scalability to millions of samples.

GBDTMPCSecure Computation

0 likes · 9 min read

Privacy-Preserving Gradient Boosting Decision Trees via Multi-Party Computation and the Squirrel Framework

AntTech

Aug 16, 2023 · Information Security

Ant Group Research Institute Presents Two First-Author Papers at USENIX Security 2023 on Secure MPC for GBDT Training and Efficient 3PC for Binary Circuits

At the 32nd USENIX Security Symposium in Anaheim, Ant Group’s Research Institute sponsored the event and showcased two first‑author papers—one introducing the Squirrel framework for fast, secure two‑party computation of Gradient Boosting Decision Trees, and another proposing an efficient 3‑party protocol for binary circuits in maliciously‑secure DNN inference.

DNN InferenceGradient BoostingMPC

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Ant Group Research Institute Presents Two First-Author Papers at USENIX Security 2023 on Secure MPC for GBDT Training and Efficient 3PC for Binary Circuits

DataFunSummit

Apr 5, 2023 · Information Security

Open Algorithm Protocol and ECDH-PSI: Background, Architecture, and Open‑Source Implementation

This article introduces the background of open algorithm protocols for heterogeneous platforms, explains the ECDH‑PSI protocol architecture—including handshake and computation phases—and presents practical open‑source implementations and usage steps for privacy‑preserving set intersection.

ECDH-PSIMPCalgorithm protocol

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Open Algorithm Protocol and ECDH-PSI: Background, Architecture, and Open‑Source Implementation

DataFunSummit

Feb 12, 2023 · Information Security

Privacy Computing: Technical Routes Overview and Ant Group’s Contributions

This article introduces and compares major privacy computing technologies—including MPC, federated learning, TEE, and proxy MPC—evaluating them across security, development cost, operational cost, accuracy, performance, participant scale, control, hardware cost, and trust, and then outlines Ant Group’s privacy computing framework, applications, and standards work.

Ant GroupData SecurityFederated Learning

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Privacy Computing: Technical Routes Overview and Ant Group’s Contributions

DataFunSummit

Nov 28, 2022 · Artificial Intelligence

Introduction to Federated Learning: Concepts, Key Technologies, and the Dianshi Federated Learning Platform

This article introduces the concept of federated learning, outlines its industry opportunities and challenges, explains the evolution of data‑sharing technologies, details core techniques such as MPC, TEE, and differential privacy, and presents the architecture and capabilities of the Dianshi federated learning platform.

AIFederated LearningMPC

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Introduction to Federated Learning: Concepts, Key Technologies, and the Dianshi Federated Learning Platform

AntTech

Sep 22, 2022 · Artificial Intelligence

SecretFlow Open‑Source Privacy Computing Framework Releases Version 0.7 with Enhanced MPC, Federated Learning, and Performance Optimizations

The SecretFlow privacy‑computing open‑source framework announced its inclusion in the PPCA Open‑Source Working Group and launched version 0.7, adding multi‑party computation, federated learning, infrastructure upgrades, and documentation improvements to advance secure AI and data analytics.

AIFederated LearningMPC

0 likes · 7 min read

SecretFlow Open‑Source Privacy Computing Framework Releases Version 0.7 with Enhanced MPC, Federated Learning, and Performance Optimizations

AntTech

Apr 8, 2022 · Artificial Intelligence

Release of Financial Application Guidance for Multi‑Party Secure Computation and Federated Learning

On March 29, the Beijing FinTech Industry Alliance published two white‑papers—‘Multi‑Party Secure Computation Financial Application Status and Implementation Guide’ and ‘Federated Learning Technology Financial Application White Paper’—detailing policies, standards, case studies, and recommendations for deploying privacy‑preserving AI technologies in the financial sector.

AIData SecurityFederated Learning

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Release of Financial Application Guidance for Multi‑Party Secure Computation and Federated Learning

DataFunTalk

Mar 30, 2022 · Information Security

A Brief History of Cryptography and the Rise of Privacy Computing

This article surveys the evolution of cryptography from ancient Mesopotamian cipher sticks through classical ciphers, the Enigma machine, modern public‑key systems, and multi‑party computation, then explains the concept, current challenges, and future directions of privacy‑preserving computation technologies.

MPCcryptographyinformation security

0 likes · 19 min read

A Brief History of Cryptography and the Rise of Privacy Computing

AntTech

Aug 18, 2020 · Artificial Intelligence

Shared Intelligence vs. Federated Learning: Techniques, Challenges, and Ant Group’s Practical Experience

The article compares shared intelligence and federated learning, examines privacy‑preserving techniques such as MPC, TEE, and differential privacy, discusses gradient‑inversion attacks and their mitigations, and presents Ant Group’s end‑to‑end system design and real‑world deployments in finance.

AI securityAnt GroupFederated Learning

0 likes · 22 min read

Shared Intelligence vs. Federated Learning: Techniques, Challenges, and Ant Group’s Practical Experience

Youku Technology

Aug 26, 2019 · Artificial Intelligence

Technical Deep Dive of Adaptive Streaming for “The Longest Day in Chang'an”: AI, Big Data, and QoE Optimization

Alibaba Entertainment’s technical deep‑dive reveals how its Smart Bitrate system leverages big‑data analytics, AI‑driven machine‑learning (including MPC and the Pensieve model) to dynamically select 5‑10‑second video segments, optimizing QoE by balancing high‑definition playback and buffering, achieving 5‑10% more HD viewing and 10‑20% fewer stalls for “The Longest Day in Chang’an.”

AIBig DataMPC

0 likes · 10 min read

Technical Deep Dive of Adaptive Streaming for “The Longest Day in Chang'an”: AI, Big Data, and QoE Optimization