Evidence map›Paper›PMID 28205005›Full record

ArticleJournal of medical systems2017

A Selective Group Authentication Scheme for IoT-Based Medical Information System.

YoHan Park, YoungHo Park

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of medical systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

  1. Findings from 2017 on Health Information ManagementYearbook of medical informatics · 2018
    Pooled it
  2. Article
  3. Article
  4. Article
  5. The Future of Cardiovascular Stents: Bioresorbable and Integrated Biosensor Technology.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2019
    Review
  6. Article
  7. 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

2 authors.

YoHan ParkSchool of Electronics Engineering, Kyungpook National University, Daegu, South Korea.
YoungHo ParkSchool of Electronics Engineering, Kyungpook National University, Daegu, South Korea. parkyh@knu.ac.kr.ORCID http://orcid.org/0000-0002-9011-8410

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The technology of IoT combined with medical systems is expected to support advanced medical services. However, unsolved security problems, such as misuse of medical devices, illegal access to the medical server and so on, make IoT-based medical systems not be applied widely. In addition, users have a high burden of computation to access Things for the explosive growth of IoT devices. Because medical information is critical and important, but users have a restricted computing power, IoT-based medical systems are required to provide secure and efficient authentication for users. In this paper, we propose a selective group authentication scheme using Shamir's threshold technique. The property of selectivity gives the right of choice to users to form a group which consists of things users select and access. And users can get an access authority for those Things at a time. Thus, our scheme provides an efficient user authentication for multiple Things and conditional access authority for safe IoT-based medical information system. To the best of our knowledge, our proposed scheme is the first in which selectivity is combined with group authentication in IoT environments.

Indexed as

AlgorithmsConfidentialityMedical Informatics ApplicationsComputer SecurityHealth Information ExchangeHumansGroup authenticationInternet of thingsMedical information systemSelectivity

Identifiers

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.