Privacy-preserving internet of things: Techniques and applications

Abstract

Privacy has become an imperative term in the recent technology developments. Lots of data are being collected through every digital activity of users. The expeditious development of IoT applications have raised the concern about the privacy of the IoT systems. The data collected via IoT sensors can reveal the daily behavior of the users, location, and other sensitive information. Hence, it is necessary to preserve the privacy of data collected by IoT devices. A large number of techniques and approaches have been implemented and used in different IoT based applications such as cloud computing based IoT, fog computing based IoT, blockchain based IoT and trajectory applications. In this paper, we present a detailed investigation of the existing approaches to preserve the privacy of data in IoT applications. The techniques like k-anonymity, secure multiparty computation, attribute based encryption and homomorphic encryption are analyzed. Finally, a comparative analysis of privacy preserving techniques with its applications are presented.