FoT-PDS: A User-Centric Paradigm for Privacy-Preserving IoT
Resumo
The Internet of Things enables pervasive and ubiquitous data collection, often without users’ awareness or consent, reinforcing the so-called privacy paradox, in which technological benefits coexist with associated privacy risks. This thesis introduces FoT-PDS, an original user-centric paradigm that integrates the Fog of Things and Personal Data Stores to empower users with data control through decentralized personal data management, granular data-access control, transparency, and enhanced privacy awareness. The proposal also includes an AI-assisted consent mechanism based on clustering methods to anticipate profiling risks and support informed consent for users. Experimental results show that FoT-PDS significantly improves perceived data control, transparency, and privacy awareness, while the latter mediates the indirect effect of data control on users’ perceived trust. Technical evaluation demonstrates the feasibility of the consent mechanism and its potential to mitigate risks associated with profiling. These insights provide empirical evidence supporting the adoption of the FoT-PDS as a viable and effective approach for promoting data control and mitigating privacy risks in the IoT context.
Referências
Campos, D., Martins, L., Mota, J., et al. (2024). Designing, implementing, and testing ai-oriented smart home applications: Challenges and best practices. In Software Architecture. ECSA 2024 Tracks and Workshops, pages 83–99, Cham. Springer Nature Switzerland.
CISCO (2019). Consumer privacy survey: The growing imperative of getting data privacy right.
Hassani, M. and Seidl, T. (2017). Using internal evaluation measures to validate the quality of diverse stream clustering algorithms. Vietnam J. of Computer Science, 4(3):171–183.
Kokolakis, S. (2017). Privacy attitudes and privacy behaviour: A review of current research on the privacy paradox phenomenon. Computers & Security, 64:122–134.
Martins, L., Campos, D., Júnior, J. M., et al. (2025). A case study of smart home development. IEEE Software, 42(6):64–73.
Mugariri, P., Abdullah, H., García-Torres, M., Parameshchari, B. D., and Abdul Sattar, K. N. (2022). Promoting information privacy protection awareness for internet of things (iot). Mobile Information Systems, 2022(1):4247651.
Pinto, G. P., Donta, P. K., Dustdar, S., and Prazeres, C. (2024). A systematic review on privacy-aware iot personal data stores. Sensors, 24:2197.
Pinto, G. P., Leles, J. R., da Costa Souza, C., de Souza, P. R., Durão, F. A., and Prazeres, C. (2025a). Model and service for privacy in decentralized online social networks. Journal of Electronic Science and Technology, 23(1):100302.
Pinto, G. P. and Prazeres, C. (2024). Towards data privacy in a fog of things. Internet Technology Letters.
Pinto, G. P. and Prazeres, C. (2025a). Data privacy in the internet of things: A perspective of personal data store-based approaches. Journal of Cybersecurity and Privacy, 5(2).
Pinto, G. P. and Prazeres, C. (2025b). A user-centric iot platform for privacy with ai-assisted consent. IEEE Open Journal of the Computer Society, 6:1834–1846.
Pinto, G. P., Sousa, N. R., Da Silva, C. N., Peixoto, M. L., Figueiredo, G. B., and Prazeres, C. V. (2025b). Enhancing iot data privacy: Ai-assisted consent mechanism in a pds-based solution. Internet of Things, 34:101807.
Pinto, G. P., Sousa, N. R., and Prazeres, C. V. (2026). My data, my rules: an experimental study on a user-centric approach to data privacy in the internet of things. Computing, 108(3):33.
Prazeres, C. and Serrano, M. (2016). SOFT-IoT: Self-Organizing FOG of Things. In 2016 30th International Conference on Advanced Information Networking and Applications Workshops, pages 803–808.
Seixas, N. F. S., Maia, A. H. O., Pinto, G. P., et al. (2025). Bridging the cost gap: A comprehensive analysis of capex and opex for smart home transition from a provider’s perspective. In Proceedings of the 10th International Conference on Internet of Things, Big Data and Security - IoTBDS, pages 27–38. INSTICC, SciTePress.
Sousa, N. R., Pinto, G. P., and Prazeres, C. V. S. (2025). Internet of things devices management for smart cities. In Proceedings of the 10th International Conference on Internet of Things, Big Data and Security - IoTBDS, pages 15–26. INSTICC, SciTePress.
Verborgh, R. (2023). Re-decentralizing the Web, for good this time. In Seneviratne, O. and Hendler, J., editors, Linking the World’s Information: Essays on Tim Berners-Lee’s Invention of the World Wide Web, pages 215–230. ACM.
Ziegeldorf, J. H., Morchon, O. G., and Wehrle, K. (2014). Privacy in the internet of things: threats and challenges. Security and Communication Networks, 7:2728–2742.
