Recent Trends toward Privacy-preservation in IoT, its Challenges and
The Internet of Things (IoT) is a self-configuring, intelligent system
in which things connect to the Internet and communicate with each other.
As “things” are autonomous and rely on a significant amount of
autonomy to carry out their individual and collective tasks, it is
possible that the autonomous environment of IoT may raise privacy
concerns. IoT encounters significant privacy and security challenges,
including inaccurate device updates, a lack of efficient privacy
solutions, user unawareness, and famed active device monitoring
capabilities. In this paper, the authors describe the background of IoT
systems and privacy and security measures, (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 Minimization, 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 less data to collect, store, and share by smart devices.
Thus, the use of Data Minimization methods in these networks can be very
beneficial for privacy-preserving, which is useful to route researchers