智隐 隐私计算平台

金智塔科技自主研发的隐私计算平台融合了多方安全计算、联邦学习、区块链等技术，提供联合建模、联合统计、匿踪查询、在线推理等服务，实现数据“可用不可见”、“用途可控可计量”，赋能数据要素安全高效流通，并促进数据要素的融合创新应用。核心能力1.联合建模：支持多方数据在不出域的前提下完成模型训练，覆盖神经网络、决策树、逻辑回归等主流算法。2.联合统计：支持多方数据在不出域的前提下完成统计，覆盖中位数、方差、偏离度等统计学指标。3.匿踪查询：数据查询时，保护查询对象的身份信息不暴露给数源方，例如身份证号、电话号码、组织机构代码等。4.在线推理：将训练完成的模型在隔离环境独立部署，支持千万级高并发、亿级大数据、毫秒级响应的场景需求。产品优势1.高安全：采用区块链、数字水印等多种技术对数据使用的全链路进行安全防护和存证，并支持国产信创，为安全提供了全方位保障。2.高性能：采用软硬一体分层架构设计，实现超大规模高效率计算，支持10方节点、亿级求交的业务场景。3.高扩展：采用全对称的分布式架构，可灵活组网无限扩展节点；支持分布式弹性扩容，高效增强算力，满足用户业务快速发展需求。4.高互通：以算法模块化、插件化的形式接入不同平台，实现数据、计算的互联互通。

The privacy computing platform independently developed by Jinzita Technology integrates technologies such as Secure Multi-Party Computation (SMPC), Federated Learning, and Blockchain, and provides services including joint modeling, joint statistics, oblivious query, and online inference. It realizes the goals of "data available but not visible" and "controllable and measurable usage", empowers the safe and efficient circulation of data elements, and promotes integrated innovative applications of data elements.

Core Capabilities
1. Joint Modeling: Supports model training using multi-party data without data leaving their local domains, covering mainstream algorithms such as Neural Networks, Decision Trees, and Logistic Regression.
2. Joint Statistics: Supports statistical computing using multi-party data without data leaving their local domains, covering statistical indicators such as Median, Variance, and Deviation.
3. Oblivious Query: Protects the identity information of the queried objects from being exposed to data source parties during data query, such as ID card numbers, phone numbers, and organization codes.
4. Online Inference: Deploys trained models independently in isolated environments, supporting scenario requirements such as 10-million-level high concurrency, 100-million-level big data processing, and millisecond-level response.

Product Advantages
1. High Security: Adopts multiple technologies such as Blockchain and Digital Watermarking to perform security protection and evidence recording for the full lifecycle of data usage, and supports domestic IT innovation and localization, providing all-round security guarantees.
2. High Performance: Adopts a hardware-software integrated layered architecture design to achieve ultra-large-scale high-efficiency computing, supporting business scenarios with 10-party nodes and 100-million-level record intersection.
3. High Scalability: Adopts a fully symmetric distributed architecture, enabling flexible networking and unlimited node expansion; supports distributed elastic scaling to efficiently enhance computing power, meeting the rapid development needs of users' businesses.
4. High Interoperability: Accesses different platforms in the form of algorithm modularization and pluginization, realizing the interoperability of data and computing.

搜集汇总

背景与挑战

背景概述

该数据集是一个隐私计算平台，提供多方安全计算、联邦学习、区块链等技术，支持联合建模、联合统计、匿踪查询和在线推理等服务，适用于金融、医疗、政务等多个应用场景。