Machine and Deep Learning Techniques in IoT and Cloud

J. Naomi, K. M., S. V.
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引用次数: 1

Abstract

In establishing a healthy environment for connectivity devices, it is essential to ensure that privacy and security of connectivity devices are well protected. The modern world lives on data, information, and connectivity. Various kinds of sensors and edge devices stream large volumes of data to the cloud platform for storing, processing, and deriving insights. An internet of things (IoT) system poses certain difficulties in discretely identifying, remotely configuring, and controlling the devices, and in the safe transmission of data. Mutual authentication of devices and networks is crucial to initiate secure communication. It is important to keep the data in a secure manner during transmission and in store. Remotely operated devices help to monitor, control, and manage the IoT system efficiently. This chapter presents a review of the approaches and methodologies employed for certificate provisioning, device onboarding, monitoring, managing, and configuring of IoT systems. It also examines the real time challenges and limitations in and future scope for IoT systems.
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物联网和云中的机器和深度学习技术
在建立健康的连接设备环境时,必须确保连接设备的隐私和安全得到很好的保护。现代世界依赖于数据、信息和互联互通。各种传感器和边缘设备将大量数据传输到云平台,用于存储、处理和获取见解。物联网(IoT)系统在离散识别、远程配置和控制设备以及安全传输数据方面存在一定困难。设备和网络的相互认证对于启动安全通信至关重要。在传输和存储过程中确保数据的安全是很重要的。远程操作的设备有助于有效地监控、控制和管理物联网系统。本章介绍了用于证书发放、设备登录、监控、管理和配置物联网系统的方法和方法。它还研究了物联网系统的实时挑战和限制以及未来的范围。
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