Evidence map›Paper›PMID 27628729›Full record

ArticleJournal of medical systems2016

A Robust and Anonymous Two Factor Authentication and Key Agreement Protocol for Telecare Medicine Information Systems.

Hu Xiong, Junyi Tao, Yanan Chen

Abstract read
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In one paragraph

Article in Journal of medical systems, 2016. 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

3 authors.

Hu XiongSchool of Information and Software Engineering, University of Electronic Science and Technology of China & State Key Laboratory of Cryptology, P.O. Box 5159, Beijing, 100878, China. xionghu.uestc@gmail.com.ORCID http://orcid.org/0000-0001-6137-6667
Junyi TaoSchool of Information and Software Engineering, University of Electronic Science and Technology of China, P.O. Box 5159, Beijing, 100878, China.
Yanan ChenThe MOE key Laboratory for Transportation Complex Systems Theory and Technology School of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nowadays people can get many services including health-care services from distributed information systems remotely via public network. By considering that these systems are built on public network, they are vulnerable to many malicious attacks. Hence it is necessary to introduce an effective mechanism to protect both users and severs. Recently many two-factor authentication schemes have been proposed to achieve this goal. In 2016, Li et al. demonstrated that Lee et al.'s scheme was not satisfactory to be deployed in practice because of its security weaknesses and then proposed a security enhanced scheme to overcome these drawbacks. In this paper, we analyze Li et al.'s scheme is still not satisfactory to be applied in telecare medicine information systems (TMIS) because it fails to withstand off-line dictionary attack and known session-specific temporary information attack. Moreover, their scheme cannot provide card revocation services for lost smart card. In order to solve these security problems, we propose an improved scheme. Then we analyze our scheme by using BAN-logic model and compare the improved scheme with related schemes to prove that our scheme is advantageous to be applied in practice.

Indexed as

Health Smart CardsComputer SecurityConfidentialityHealth Information ExchangeHumansInformation SystemsNonlinear DynamicsTelemedicineAuthenticationExtended chaotic mapsMulti-server environmentSession key agreementSmart cardTMIS

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.