Privacy preservation of Internet of Things–integrated social networks: a survey and future challenges
Sara Salim, Nour Moustafa, Benjamin Turnbull · International Journal of Web Information Systems · 2025
Purpose This paper aims to provide a comprehensive understanding of the evolving landscape of Privacy Preservation (PP) techniques within the context of Web 3.0, where Social Media (SM) integrated with Internet of Things (IoT). It explores the challenges and opportunities inherent in safeguarding user privacy amidst the convergence of these technologies, with a focus on examining the efficacy of existing PP methods and identifying areas for further research and development. Design/methodology/approach This study adopts a structured approach, beginning with a detailed overview of SM, IoT and the data generated by IoT-integrated SM networks, emphasising their significance in contemporary applications. It proceeds to explore privacy concerns specific to these networks, followed by an exhaustive analysis of PP techniques, including Differential Privacy (DP), Federated Learning (FL) and blockchain. In addition, this study examines prevalent cyber threats and vulnerabilities related to PP in IoT-integrated SM networks, providing insights into emerging challenges and the need for robust security measures. Findings The analysis reveals the critical importance of PP in striking a delicate balance between harnessing the benefits of enhanced connectivity and data insights while ensuring the protection of user privacy. DP, FL and blockchain emerge as prominent techniques for PP, each offering unique advantages and limitations in preserving user privacy within IoT-integrated SM networks. Moreover, this study underscores the dynamic nature of the threat landscape, necessitating continual adaptation and innovation in cybersecurity practices to mitigate evolving risks effectively. Originality/value This paper contributes to the existing literature by offering a comprehensive and structured overview of PP techniques tailored specifically to the context of IoT-integrated SM networks. By synthesising insights from diverse sources and providing a detailed understanding of the challenges and opportunities in PP, it advances the ongoing discussion on privacy in the digital age. Furthermore, by outlining future research directions, this paper encourages further inquiry and innovation in safeguarding user privacy within IoT-integrated environments.