Privacy Preservation in the Internet of Things: A Scoping Review and Future Research Directions
Keywords:
Internet of Things (IoT), Privacy-Preserving, Security, Privacy, TaxonomyAbstract
Privacy preservation is a critical concern in Internet of Things (IoT) systems due to the rapid expansion of connected devices and sensitive data exchange. Numerous studies have proposed privacy-preserving techniques (PPTs) to counter threats. However, a structured synthesis of these developments has been limited. This scoping review, conducted following PRISMA guidelines, analyzed literature published between 2010 and 2024. Data was collected from six databases, yielding 1,394 studies, of which 260 met predefined eligibility criteria related to privacy mechanisms, IoT layers and application domains. We identified three major categories of PPTs: cryptographic techniques, anonymization and obfuscation methods and decentralized trust models. Results show that most studies focus on e-health and industrial IoT domains, while device identity privacy remains underexplored. Persistent challenges include computational overhead, scalability and data utility trade-offs, particularly in cryptographic and blockchain-based solutions. The review proposes a taxonomy of PPTs and emphasizes the need for lightweight, scalable and trust-free frameworks such as the emerging “Blind Approach.” These findings provide a foundation for advancing efficient and privacy-preserving IoT architectures.
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