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This paper presents a novel clustering-based anonymization scheme for privacy-preserving data collection in IoT-based healthcare services, addressing significant privacy concerns associated with the transmission of sensitive patient data. The proposed method utilizes a client-server-to-user model and incorporates a modified clustering-based k-anonymity approach to effectively anonymize data while minimizing communication costs and mitigating various privacy attacks. The effectiveness and efficiency of the s

Author

jersmitpity

Language

EN