Systematic Literature Review on Data Provenance in Internet of Things

Abstract

Internet of Things(IoT) is a concept that develops day by day and is now an indispensable part of our lives. Although it has been developed a lot, it still has many problematic areas and has many aspects that need improvement. On the other hand, data provenance is a concept that covers the origin of the data, the changes made, and the processes it has gone through. Data provenance is an essential option for improvements in the IoT field. Although there are many research studies in the literature related to the use of data provenance in the IoT, we could not identify a comprehensive systematic literature review that focuses explicitly on this topic. The study aims to examine the current data provenance on the Internet of Things studies, identify potential shortcomings or improvements, determine the working areas that can be done to make the processes more efficient and solve the IoT and data provenance problems. We also aim to serve this study as a knowledge base for researchers for conducting further research and development in this area. The review is done by following a systematic literature review process. We presented an SLR-based method on data provenance in IoT. We investigated the challenges encountered in IoT applications and worked on using data provenance as a solution. We conducted a literature search covering the years 2012-2022. We found 140 published papers. After applying exclusion criteria for these papers, we have focused on the final 16 papers. In the IoT area, some challenges require work, such as constrained resources, heterogeneity, scalability, mobility, security and privacy. Our study shows that data provenance is primarily used in security, privacy, reliability, and trust. We can say that the studies in these fields have increased gradually over the last years. Blockchain is frequently used to provide data provenance.