Towards data privacy in a fog of things

Pinto, George Pacheco; Prazeres, Cassio

doi:10.1002/itl2.512

Cited by 2 publications

(2 citation statements)

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“…As part of our future work, we aim to further develop our PDS-based solution [83] to address privacy issues in the context of Fog of Things [84] data [85]. We advocate for a user-centric approach, and assert that it can mitigate various privacy issues through an approach that enhances users' control while improving transparency, awareness, and trust.…”

Section: Discussionmentioning

confidence: 99%

“…PDS enhances user control, allowing users to store, manage, and share personal data and digital assets while controlling access and utilization. For example, as proposed by Pinto and Prazeres [83], decentralized data processing can be utilized to place control over decisions regarding data treatment in the hands of each user. Their proposal embraces a Personal Data Store within an IoT/FoT architecture, positioning the user at the core of decision-making and empowering them to determine under what circumstances, by whom, and to what extent their data will be processed.…”

Section: Information Leakagementioning

confidence: 99%

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A Systematic Review on Privacy-Aware IoT Personal Data Stores

Pinto,

Donta,

Dustdar

et al. 2024

Sensors

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Information Leakagementioning

confidence: 99%