Privacy Preserving Computations over Healthcare Data

Wang, Qi; Zhou, Dehua; Yang, Shiyin; Wang, Chuansheng; Guan, Quanlong

doi:10.1109/ithings/greencom/cpscom/smartdata.2019.00123

Cited by 9 publications

(4 citation statements)

References 24 publications

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“…• Homomorphic encryption: Healthcare data can be analyzed in encrypted form to preserve privacy while valuable insights can be extracted [130]. • Anti-man-in-the-middle and anti-replay attack security attributes: Blockchain-based solution can prevent personal health data tampering and protect privacy effectively [131].…”

Section: Legal and Technologicalmentioning

confidence: 99%

A Bibliometric Analysis of Technology in Digital Health: Exploring Health Metaverse and Visualizing Emerging Healthcare Management Trends

Nguyen,

Voznak

2024

IEEE Access

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Section: Legal and Technologicalmentioning

confidence: 99%

A Bibliometric Analysis of Technology in Digital Health: Exploring Health Metaverse and Visualizing Emerging Healthcare Management Trends

Nguyen,

Voznak

2024

IEEE Access

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“…In 2019, Wang et al [18] combined homomorphic encryption and proxy reencrytion technology to implement outsourcing computing solutions in healthcare systems. In this solution, there are several clients with different public keys, an electronic medical cloud platform, and an auxiliary cloud server.…”

Section: Related Workmentioning

confidence: 99%

A Blockchain-Based Privacy Preservation Scheme in Mobile Medical

Hai-ying

Wei

et al. 2022

Security and Communication Networks

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With the rapid development of mobile medical, how to establish an effective security mechanism to protect data security and privacy while users enjoy medical services has become an urgent problem to be solved. Aiming at the easy leakage of privacy in mobile medical terminals and untrustworthy data, we make use of a role-separated mechanism to generate trusted anonymous certificates. We propose a lightweight identity authentication scheme and adopt blockchain to protect the security of medical data. Meanwhile, in view of the problems of transparency and visibility of blockchain information, we adapt the searchable encryption algorithm to realize ciphertext processing in the whole life cycle. Experiments show that our scheme can reduce the cost of computation on the basis of ensuring traffic. In the process of dynamic updating of ciphertext keywords, except the keyword identifier, less information is leaked to the server, which protects privacy of users.

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“…Furthermore, intending to protect patients' sensitive data while the smart health platform needs to do some analysis over these data, researchers Wang et al [60] proposed a privacy-preserving outsourced computation scheme in the healthcare system. ey enhanced the security of this scheme by splitting the decryption permissions into both servers.…”

Section: Centralized Architecturementioning

confidence: 99%

The Systematic Literature Review of Privacy-Preserving Solutions in Smart Healthcare Environment

Majdoubi

Bakkali

Sadki

et al. 2022

Security and Communication Networks

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The rapid development of the Internet of Medical Things (IoMT) technology has resulted in various advances in the smart healthcare field; it improves healthcare systems to offer more complicated real-time services and provides an efficient patient motioning system. However, despite the brilliant side of IoMT, several concerns continue to undercut its adoption. In fact, collecting, transmitting, storing, and using data in IoMT applications raises issues regarding privacy and data protection, especially with the multitude of stakeholders involved during the whole data life cycle. Motivated from these facts, this article is devoted to perform a Systematic Literature Review (SLR) of privacy-preserving solutions used in the smart healthcare ecosystem. The recent research papers disseminated between 2017 and 2021 are selected from multiple databases and a standardized SLR method is conducted. A total of 100 papers were reviewed and a critical analysis was conducted on the selected papers. Moreover, this review study attempts to highlight the limitation of the current approaches and aims to find possible solutions to them. Thus, a detailed analysis was carried out on the selected papers in terms of the privacy techniques they deployed, the data life cycle phase they addressed, the stakeholders needs they met, and the privacy principles they covered according to privacy laws and regulations. Finally, we summarize our results showing privacy-preserving trends and identifying recommendations to involve privacy principles coverage in smart healthcare applications.

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Privacy Preserving Computations over Healthcare Data

Cited by 9 publications

References 24 publications

A Bibliometric Analysis of Technology in Digital Health: Exploring Health Metaverse and Visualizing Emerging Healthcare Management Trends

A Bibliometric Analysis of Technology in Digital Health: Exploring Health Metaverse and Visualizing Emerging Healthcare Management Trends

A Blockchain-Based Privacy Preservation Scheme in Mobile Medical

The Systematic Literature Review of Privacy-Preserving Solutions in Smart Healthcare Environment

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