隐私计算技术在铁路行业应用刍议

Preliminary discussion on the application of privacy computing technology in railway

随着工业互联网背景下各行业数据融合加快,铁路信息系统业务涵盖范围的不断拓展,与外部实现跨域业务数据流通的需求不断增加,供应链数据安全也逐渐成为铁路数字安全体系中的一个关切点。隐私计算作为保障数据安全流通的重要技术,以其“数据可用不可见”的交易优势,可以有效解决铁路与供应链企业间数据流通安全的问题。文章对隐私计算的安全多方计算、联邦学习、可信执行环境等技术进行研究分析,参考隐私计算相关标准,提出铁路隐私计算技术架构,初步探讨隐私计算技术在铁路行业供应链中应用,以期为铁路企业与外部业务相关方开展数据共享应用提供安全屏障,促进铁路数据跨域安全高效流通,进一步发挥数据价值倍增和溢出效应。

With the acceleration of data integration in various industries under the background of industrial Internet,the continuous expansion of the coverage of railway information system business,and the increasing demand for external cross domain business data circulation,supply chain data security has gradually become a concern of railway digital security systems.Privacy computing,as an important technology to ensure the secure flow of data,can effectively solve the problem of data flow security between railway and supply chain enterprises with its transaction advantage of"data available but invisible".The article conducts research and analysis on secure multi-party computing,federated learning,trusted execution environment and other technologies related to privacy computing.Referring to relevant standards of privacy computing,it proposes a railway privacy computing technology architecture and explores the application of privacy computing technology in the railway industry supply chain.The aim is to provide a security barrier for railway enterprises and external business stakeholders to carry out data sharing applications,promote cross domain secure and efficient flow of railway data,and further leverage the value doubling and spillover effects of the data.