Evidence map›Paper›PMID 24158427›Full record

ArticleJournal of medical systems2013

Privacy preserving index for encrypted electronic medical records.

Yu-Chi Chen, Gwoboa Horng, Yi-Jheng Lin, Kuo-Chang Chen

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of medical systems, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Privacy Policy and Technology in Biomedical Data Science.Annual review of biomedical data science · 2018
    Article
  2. Article
  3. Article
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

4 authors.

Yu-Chi ChenDepartment of Computer Science and Engineering, National Chung Hsing University, Taichung, Taiwan, wycchen@ieee.org.
Gwoboa Horng
Yi-Jheng Lin
Kuo-Chang Chen

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the development of electronic systems, privacy has become an important security issue in real-life. In medical systems, privacy of patients' electronic medical records (EMRs) must be fully protected. However, to combine the efficiency and privacy, privacy preserving index is introduced to preserve the privacy, where the EMR can be efficiently accessed by this patient or specific doctor. In the literature, Goh first proposed a secure index scheme with keyword search over encrypted data based on a well-known primitive, Bloom filter. In this paper, we propose a new privacy preserving index scheme, called position index (P-index), with keyword search over the encrypted data. The proposed index scheme is semantically secure against the adaptive chosen keyword attack, and it also provides flexible space, lower false positive rate, and search privacy. Moreover, it does not rely on pairing, a complicate computation, and thus can search over encrypted electronic medical records from the cloud server efficiently.

Indexed as

ConfidentialityAlgorithmsComputer SecurityElectronic Health RecordsHumans

Identifiers

What OpenQuestion holds

Textmetadata
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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 OpenQuestion graph.