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@article{173965,
        author = {M.Padmavathi},
        title = {Enhancing Privacy and Utility in IoT Data Sharing: A Multi-Layered Privacy-Preserving Raw Data Publishing Approach},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {2252-2256},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=173965},
        abstract = {In the Internet of Things (IoT), data sharing and publishing play a crucial role in analyzing network environments and improving the Quality of Service (QoS). However, to encourage data providers (i.e., IoT end-users) to contribute their data, privacy requirements must be addressed when collecting and publishing this data. Traditional privacy-preserving techniques, such as k-anonymity, data aggregation, and differential privacy, typically modify, aggregate, or add noise to data, which results in a loss of utility. To mitigate this issue, privacy-preserving raw data publishing offers a promising solution by ensuring the unlinkability of data from its source. System presents a lightweight raw data collection scheme that guarantees both the rawness and unlinkability of the data using Shamir's secret sharing and a shuffling algorithm. The proposed scheme ensures that the raw data remains intact while maintaining privacy through secure distribution across multiple parties. Moreover, the performance evaluation demonstrates that this approach is feasible and practical for IoT environments.
To further enhance the security and privacy of the proposed scheme, a multi-layered approach is introduced. This approach integrates advanced cryptographic techniques, decentralized storage, secure authentication, and access control mechanisms. While Shamir’s secret sharing and the shuffling algorithm provide a robust foundation for privacy protection, the additional security layers significantly strengthen the overall scheme. Cryptographic techniques such as public-key encryption, coupled with decentralized storage solutions, minimize the risk of centralized data breaches. Furthermore, secure authentication and granular access control ensure that only authorized entities can access or modify the data. The combination of these measures results in a secure, privacy-preserving, and efficient solution for raw data publishing in IoT environments, balancing both privacy and utility without compromising data integrity. This enhancement ultimately contributes to fostering trust and participation in IoT-based data sharing ecosystems.},
        keywords = {Internet of Things (IoT), Data Sharing, Privacy-Preserving, Quality of Service (QoS), Raw Data Publishing, Shamir’s Secret Sharing, Shuffling Algorithm, Data Unlink ability, Cryptographic Techniques, Decentralized Storage, Secure Authentication, Access Control, Privacy Protection, Data Integrity, Trust and Participation, IoT Security, Distributed Privacy Preservation, IoT Data Sharing Ecosystem, Advanced Cryptography, Multi-layered Privacy Approach.},
        month = {March},
        }