蚂蚁隐私计算智能服务平台

    隐私计算智能服务平台（PPC）是以联邦学习FL、安全多方计算MPC、可信硬件执行环境TEE等隐私数据保护技术工具为基础服务的平台。核心价值在于保证原始数据不出本地即可完成多方数据联合建模和联合计算能力，同时支持安全隐私保护集合求交、安全隐私查询、安全统计分析。实现各合作机构数据在流通、计算过程中，端到端的安全保护和可审计， 推动跨行业的可信数据价值的融合和协同，很好地解决了业界数据孤岛的难题。

The Privacy-Preserving Computing Intelligent Service Platform (PPC) is a platform built on foundational services of privacy data protection technologies including Federated Learning (FL), Secure Multi-Party Computation (MPC), and Trusted Execution Environment (TEE). Its core value lies in enabling joint multi-party data modeling and computing without requiring raw data to leave the local sites of cooperating institutions, while also supporting secure privacy-preserving set intersection, secure privacy-aware querying, and secure statistical analysis. It achieves end-to-end security protection and auditability for data from cooperating institutions throughout the entire process of data circulation and computing, promotes the integration and collaboration of trusted data value across industries, and effectively addresses the industry-wide challenge of data silos.

搜集汇总

背景与挑战

背景概述

蚂蚁隐私计算智能服务平台（PPC）基于联邦学习、安全多方计算和可信硬件执行环境等技术，提供数据不出本地的联合建模与计算能力，支持隐私保护集合求交、查询和统计分析，实现跨机构数据安全流通与协同。