Recent trends towards privacy-preservation in Internet of Things, its challenges and future directions

【Author】 Yaraziz, Mahdi Safaei; Jalili, Ahmad; Gheisari, Mehdi; Liu, Yang

【Source】IET CIRCUITS DEVICES & SYSTEMS

【影响因子】1.269

【Abstract】The Internet of Things (IoT) is a self-configuring, intelligent system in which autonomous things connect to the Internet and communicate with each other. As 'things' are autonomous, it may raise privacy concerns. In this study, the authors describe the background of IoT systems and privacy and security measures, including (a) approaches to preserving privacy in IoT-based systems, (b) existing privacy solutions, and (c) recommending privacy models for different layers of IoT applications. Based on the results of our study, it is clear that new methods such as Blockchain, Machine Learning, Data Minimisation, and Data Encryption can greatly impact privacy issues to ensure security and privacy. Moreover, it makes sense that users can protect their personal information easier if there is fewer data to collect, store, and share by smart devices. Thus, this study proposes a machine learning-based data minimisation method that, in these networks, can be very beneficial for privacy-preserving.

【Keywords】data flow analysis; data handling; data privacy; Internet of Things; security of data

【发表时间】

【收录时间】2023-01-15

【文献类型】观点阐述

【主题类别】

区块链技术-协同技术-物联网