ArticleComputational and mathematical methods in medicine2013
Privacy-preserving health data collection for preschool children.
Article in Computational and mathematical methods in medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed, 8 citations in OpenAlex.
- (a,k)-Anonymous Scheme for Privacy-Preserving Data Collection in IoT-based Healthcare Services Systems.Journal of medical systems · 2018Article
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the development of network technology, more and more data are transmitted over the network and privacy issues have become a research focus. In this paper, we study the privacy in health data collection of preschool children and present a new identity-based encryption protocol for privacy protection. The background of the protocol is as follows. A physical examination for preschool children is needed every year out of consideration for the children's health. After the examination, data are transmitted through the Internet to the education authorities for analysis. In the process of data collection, it is unnecessary for the education authorities to know the identities of the children. Based on this, we designed a privacy-preserving protocol, which delinks the children's identities from the examination data. Thus, the privacy of the children is preserved during data collection. We present the protocol in detail and prove the correctness of the protocol.
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Registered trials
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 OpenQuestion graph.