Fuzzy-Logic-Based Privacy-Aware Dynamic Release of IoT-Enabled Healthcare Data

Hasina Attaullah, Tehsin Kanwal, Adeel Anjum, Ghufran Ahmed, Suleman Khan, Danda B. Rawat*, Rizwan Khan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The recent evolution of the Internet of Things in the healthcare sector has attained substantial recognition from the government and industry. Healthcare data accumulated from diverse sources are stored by health service providers which is useful for patient diagnosis as well as for research for pivotal analysis. However, healthcare data contains sensitive information of an individual that needs to be protected. The sensitive health information of an individual contains multiple attributes and the correlation of this information may lead to a privacy breach. In more complex scenarios, such type of data is expected to be released periodically and dynamically, the privacy breach of individuals becomes imminent due to the presence of personal data. In this article, a fuzzy logic-based intelligent privacy-aware algorithm is proposed to protect the individual's privacy with multiple sensitive attributes in a dynamic data release scenario. Our formal modeling and analysis show that the proposed approach offers a robust privacy guarantee while releasing health-related data. Furthermore, the empirical evaluation exhibits that the proposed model outperforms the state-of-the-art approaches in terms of information loss and query accuracy.

Original languageEnglish
Pages (from-to)4411-4420
Number of pages10
JournalIEEE Internet of Things Journal
Volume9
Issue number6
Early online date10 Aug 2021
DOIs
Publication statusPublished - 15 Mar 2022

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