论文标题

为金融行业提供5G启用物联网的数据分析的隐私保护

Privacy Preserving Data Analytics in 5G-Enabled IoT for the Financial Industry

论文作者

Lim, Cheng Lock

论文摘要

下一代无线网络(例如5G)承诺更快的速度,延迟延迟以及连接更多设备的能力。 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应用程序系统到微服务中,以在分布式边缘服务器上进行部署,从而减少网络延迟和改善服务。这些运动在保护访问点之间的业务数据的安全性和隐私方面构成了挑战。本文介绍了一种新的架构和协议,以解决金融行业的用例。该解决方案假设在边缘服务器上部署信用评估模型。该模型接受和流程加密的数据,该数据由寻求在线信用评估的潜在客户提交。加密的评估结果被发送给客户进行解密和解释。数据传输横跨异步通信,并且数据保护使用同态加密。概念验证实验表明,可以在较短的响应时间和合理的预测准确性中实现所提出的方法。

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.

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