Next-generation wireless networks like 5G promise faster speed, shorter latency, and the ability to connect more devices. Such benefits are set to make drastic changes to the future society, empowering smart cities, enabling autonomous cars, enhancing business processes, changing consumer behaviors, etc. In the financial industry, banks evaluate the deployment of Internet of Things (IoT) technologies and edge computing for better customer engagement, e.g., mobile branches on a vehicle, micro-ATM, self-service digital panel, etc. One of the trends is breaking down monolithic business application systems into micro-services for deployment on distributed edge servers, thus reducing network latency and improving services. Such movements pose challenges in protecting the security and privacy of business data between access points. This paper introduces a new architecture and protocol to tackle a use case for the financial industry. The solution assumes deploying a credit assessment model on an edge server. The model accepts and processes encrypted data submitted by potential customers seeking online credit assessments. The encrypted assessment results are sent back to the customers for decryption and interpretation. The data transmission rides on asynchronous communication, and the data protection uses Homomorphic Encryption. A proof-of-concept experiment shows that the proposed method can be achieved with a short response time and a reasonable prediction accuracy.
翻译:下一代无线网络,如5G承诺更快的速度、更短的延缓时间和连接更多装置的能力。这些好处将给未来社会带来巨大的变化,赋予智能城市权力,扶持自治汽车,加强业务流程,改变消费者行为等。在金融业,银行评估互联网(IoT)技术的部署和边际计算,以更好地与客户接触,例如汽车上的移动分支、微型自动自动取款机、自助数字板等。趋势之一是将单体商业应用系统破碎为微型服务,用于在分布式边缘服务器上部署,从而减少网络延缓和改进服务。这种流动在保护接入点之间的商业数据安全和隐私方面构成挑战。本文介绍了处理金融业使用案例的新架构和协议。解决方案假定在边端服务器上部署信用评估模型。模型接受并处理寻求在线信用评估的潜在客户提交的加密数据。加密的评估结果将发送给客户进行解密和解读。数据传输数据将进行同步通信,从而减少网络的延迟性,并改进服务。数据传输过程将使用一个可靠的时间预测方法,从而实现对数据进行测试。