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README
Apache-2.0

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由密码学专家团队打造的开源隐私计算平台

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中文 | English

隐私计算

数据流动起来才可以创造更大的价值,随着数字经济持续高速增长,数据的互联互通需求越来越旺盛,大到政府机关的机密数据、公司核心商业数据、小到个人信息。近两年,我国也相继出台了 《数据安全法》《个人信息保护法》。因此,如何让数据安全地流通起来,是一个必须要解决的问题

隐私计算技术作为连接数据流通和隐私保护法规的纽带,实现了 “数据可用不可见”。即在保护数据本身不对外泄露的前提下实现数据分析计算的技术集合。隐私计算作为数据流通的重要创新前沿技术,已经广泛应用于金融、医疗、通信、政务等多个行业。

PrimiHub

如果你对隐私计算感兴趣,想近距离体验下隐私计算的魅力,不妨试试 PrimiHub!一款由密码学专家团队打造的开源隐私计算平台,它安全可靠、开箱即用、自主研发、功能丰富。

特性

  • 开源:完全开源、免费
  • 安装简单:支持 Docker 一键部署
  • 开箱即用:拥有 Web界面命令行Python SDK 多种使用方式
  • 功能丰富:支持隐匿查询、隐私求交、联合统计、数据资源管理等功能
  • 灵活配置:支持自定义扩展语法、语义、安全协议等
  • 自主研发:基于安全多方计算、联邦学习、同态加密、可信计算等隐私计算技术

快速开始

推荐使用 Docker 部署 PrimiHub,开启你的隐私计算之旅。

# 第一步:下载
git clone https://github.com/primihub/primihub.git
# 第二步:启动容器
cd primihub && docker-compose up -d
# 第三步:进入容器
docker exec -it primihub-node0 bash
# 第四步:执行隐私求交计算
./primihub-cli --task_config_file="example/psi_ecdh_task_conf.json"
I20230616 13:40:10.683375    28 cli.cc:524] all node has finished
I20230616 13:40:10.683745    28 cli.cc:598] SubmitTask time cost(ms): 1419
# 查看结果
cat data/result/psi_result.csv
"intersection_row"
X3
...

PSI

隐私求交例子 在线尝试命令行

除此之外,PrimiHub 还提供了多种适合不同人群的使用方式:

问题 / 帮助 / Bug

如果您在使用过程中遇到任何问题,需要我们的帮助可以 点击 反馈问题。

欢迎添加我们的微信助手,加入「PrimiHub 开源社区」微信群。“零距离”接触项目核心开发、密码学专家、隐私计算行业大咖,获得更及时的回复和隐私计算的第一手资讯。

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许可证

此代码在 Apache 2.0 下发布,参见 LICENSE 文件。

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由密码学专家团队打造的开源隐私计算平台,支持安全多方计算、联邦学习、隐私求交、隐私查询等。 展开 收起
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