Privacy-preserving smart IoT-based healthcare big data storage and self-adaptive access control system
By Yang Yang, Xianghan Zheng, Wenzhong Guo, Ximeng Liu, Victor Chang. Information Sciences, 2018
320 citations recorded by the source corpus.
Abstract In this paper, a privacy-preserving smart IoT-based healthcare big data storage system with self-adaptive access control is proposed. The aim is to ensure the security of patients’ healthcare data, realize access control for normal and emergency scenarios, and support smart deduplication to save the storage space in big data storage system. The medical files generated by the healthcare IoT network are encrypted and transferred to the storage system, which can be securely shared among the healthcare staff from different medical domains leveraging a cross-domain access control policy. The traditional access control technology allows the authorized data users to decrypt patient’s sensitive medical data, but also hampers the first-aid treatment when the patient’s life is threatened because the on-site first-aid personnel are not permitted to get patient’s historical medical data. To deal with this dilemma, we propose a secure system to devise a novel two-fold access control mechanism, which is self-adaptive for both normal and emergency situations. In normal application, the healthcare staff with proper attribute secret keys can have the data access privilege; in emergency application, patient’s historical medical data can be recovered using a password-based break-glass access mechanism. To save the storage overhead in the big data storage system, a secure deduplication method is designed to eliminate the duplicate medical files with identical data, which may be encrypted with different access policies. A highlight of this smart secure deduplication method is that the remaining medical file after the deduplication can be accessed by all the data users authorized by the different original access policies. This smart healthcare big data storage system is formally proved secure, and extensive comparison and simulations demonstrate its efficiency.
Subfields: Artificial Intelligence, Information Systems
View Paper: https://www.semanticscholar.org/paper/3ec9404cf3b8be85348b8145973328ce62698f7c
How researchers see this paper
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In Artificial Intelligence
- Ekram Hossain
- N. Xiong
- Syed Ali Hassan
- Athanasios V. Vasilakos
- Pan Yang
- Rasheed Hussain
- Jingli Ren
- Fatima Hussain
In Information Systems
Citations in the corpus
- Machine Learning in IoT Security: Current Solutions and Future Challenges (2019, background): “[119] proposed an adaptive access control mechanism for personal health records data stored in a cloud in encrypted form.”
- The Future of Healthcare Internet of Things: A Survey of Emerging Technologies (2020, background): “In [182], a system is proposed for providing limited access to emergency personnel, while greater access is provided for other healthcare facilities.”
- Data Security and Privacy Protection for Cloud Storage: A Survey (2020, background): “In order to realize temporary access authorization in the process of cross domain data sharing, Yang et al. [101] presented a self-adaptive access control system with secure deduplication.”