Evidence map›Paper›PMID 33886662›Full record

ArticlePloS one2021

Improved privacy preserving method for periodical SRS publishing.

Wei Huang, Tong Yi, Haibin Zhu, Wenqian Shang, Weiguo Lin

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Wei HuangDivision of Scientific Research, Communication University of China, Beijing, China.
Tong YiSchool of computer information and Engineering, Guangxi Normal University, Guilin, Guangxi, China.ORCID 0000-0003-0946-5237
Haibin ZhuDepartment of Computer Science and Mathematics, Nipissing University, North Bay, Ontario, Canada.
Wenqian ShangSchool of Computer Science, Communication University of China, Beijing, China.
Weiguo LinSchool of Computer Science, Communication University of China, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spontaneous reporting systems (SRSs) are used to collect adverse drug events (ADEs) for their evaluation and analysis. Periodical SRS data publication gives rise to a problem where sensitive, private data can be discovered through various attacks. The existing SRS data publishing methods are vulnerable to Medicine Discontinuation Attack(MD-attack) and Substantial symptoms-attack(SS-attack). To remedy this problem, an improved periodical SRS data publishing-PPMS(k, θ, ɑ)-bounding is proposed. This new method can recognize MD-attack by ensuring that each equivalence group contains at least k new medicine discontinuation records. The SS-attack can be thwarted using a heuristic algorithm. Theoretical analysis indicates that PPMS(k, θ, ɑ)-bounding can thwart the above-mentioned attacks. The experimental results also demonstrate that PPMS(k, θ, ɑ)-bounding can provide much better protection for privacy than the existing method and the new method dose not increase the information loss. PPMS(k, θ, ɑ)-bounding can improve the privacy, guaranteeing the information usability of the released tables.

Indexed as

Medical RecordsPrivacyAdverse Drug Reaction Reporting SystemsAlgorithmsHumansInterior Design and FurnishingsResearch DesignSerial Publications

Identifiers

PMID33886662
PMCPMC8691852

What OpenQuestion holds

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LicenceCC BY
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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.