Key points are not available for this paper at this time.
Data from the Internet of Things (IoT) enables the design of new business models and services that improve user experience and satisfaction. These data serve as important information sources for many domains, including disaster management, biosurveillance, smart cities, and smart health, among others. However, this scenario involves the collection of personal data, raising new challenges related to data privacy protection. Therefore, we aim to provide state-of-the-art information regarding privacy issues in the context of IoT, with a particular focus on findings that utilize the Personal Data Store (PDS) as a viable solution for these concerns. To achieve this, we conduct a systematic mapping review to identify, evaluate, and interpret the relevant literature on privacy issues and PDS-based solutions in the IoT context. Our analysis is guided by three well-defined research questions, and we systematically selected 49 studies published until 2023 from an initial pool of 176 papers. We analyze and discuss the most common privacy issues highlighted by the authors and position the role of PDS technologies as a solution to privacy issues in the IoT context. As a result, our findings reveal that only a small number of works (approximately 20%) were dedicated to presenting solutions for privacy issues. Most works (almost 82%) were published between 2018 and 2023, demonstrating an increased interest in the theme in recent years. Additionally, only two works used PDS-based solutions to deal with privacy issues in the IoT context.
Building similarity graph...
Analyzing shared references across papers
Loading...
George Pacheco Pinto
Universidade Federal da Bahia
Praveen Kumar Donta
Stockholm University
Schahram Dustdar
University of Applied Sciences Technikum Wien
Sensors
TU Wien
Universidade Federal da Bahia
Instituto Federal da Bahia
Building similarity graph...
Analyzing shared references across papers
Loading...
Pinto et al. (Fri,) studied this question.
synapsesocial.com/papers/6a102a0f9e54838161fdd92b — DOI: https://doi.org/10.3390/s24072197