Evidence map›Paper›PMID 38169943›Full record

ArticleHeliyon2024

Dual blockchain-based data sharing mechanism with privacy protection for medical internet of things.

Linchen Liu, Ruyan Liu, Zhiying Lv, Ding Huang, Xing Liu

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Linchen LiuDepartment of Rheumatology, Zhongda Hospital, School of Medicine, Southeast University, 210009, Nanjing, Jiangsu, China.
Ruyan LiuEngineering Research Center of Digital Forensics of Ministry of Education, School of Computer Science, Nanjing University of Information Science and Technology, 210044, Nanjing, Jiangsu, China.
Zhiying LvEngineering Research Center of Digital Forensics of Ministry of Education, School of Computer Science, Nanjing University of Information Science and Technology, 210044, Nanjing, Jiangsu, China.
Ding HuangEngineering Research Center of Digital Forensics of Ministry of Education, School of Computer Science, Nanjing University of Information Science and Technology, 210044, Nanjing, Jiangsu, China.
Xing LiuSchool of Medicine, Southeast University, 210009, Nanjing, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the period of big data, the Medical Internet of Things (MIoT) serves as a critical technology for modern medical data collection. Through medical devices and sensors, it enables real-time collection of a large amount of patients' physiological parameters and health data. However, these data are often generated in a high-speed, large-scale, and diverse manner, requiring integration with traditional medical systems, which further exacerbates the phenomenon of scattered and heterogeneous medical data. Additionally, the privacy and security requirements for the devices and sensor data involved in the MIoT are more stringent. Therefore, when designing a medical data sharing mechanism, the data privacy protection capability of the mechanism must be fully considered. This paper proposes an alliance chain medical data sharing mechanism based on a dual-chain structure to achieve secure sharing of medical data among entities such as medical institutions, research institutions, and cloud privacy centers, and at the same time provide privacy protection functions to achieve a balanced combination of privacy protection capability and data accessibility of medical data. First, a knowledge technology based on ciphertext policy attribute encryption with zero-knowledge concise non-interactive argumentation is used, combined with the data sharing structure of the federation chain, to ensure the integrity and privacy-protecting capability of medical data. Second, the approach employs certificate-based signing and proxy re-encryption technology, ensuring that entities can decrypt and verify medical data at the cloud privacy center using this methodology, consequently addressing the confidentiality concerns surrounding medical data. Third, an efficient and secure key identity-based encryption protocol is used to ensure the legitimacy of user identity and improve the security of medical data. Finally, the theoretical and practical performance analysis proves that the mechanism is feasible and efficient compared with other existing mechanisms.

Indexed as

BlockchainMedical data sharingMedical internet of thingsPrivacy protection

Identifiers

PMID38169943
PMCPMC10758875

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.