Evidence map›Paper›PMID 26399937›Full record

ArticleJournal of medical systems2015

An Improved and Secure Biometric Authentication Scheme for Telecare Medicine Information Systems Based on Elliptic Curve Cryptography.

Shehzad Ashraf Chaudhry, Khalid Mahmood, Husnain Naqvi, Muhammad Khurram Khan

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Article in Journal of medical systems, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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.

Shehzad Ashraf ChaudhryDepartment of Computer Science and Software Engineering, International Islamic University, Islamabad, Pakistan. shahzad@iiu.edu.pk.ORCID http://orcid.org/0000-0002-9321-6956
Khalid MahmoodDepartment of Computer Science and Software Engineering, International Islamic University, Islamabad, Pakistan. khalid.phdcs74@iiu.edu.pk.
Husnain NaqviDepartment of Computer Science and Software Engineering, International Islamic University, Islamabad, Pakistan. husnain.naqvi@iiu.edu.pk.
Muhammad Khurram KhanCenter of Excellence in Information Assurance, King Saud University, Riyadh, Saudi Arabia. mkhurram@ksu.edu.sa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Telecare medicine information system (TMIS) offers the patients convenient and expedite healthcare services remotely anywhere. Patient security and privacy has emerged as key issues during remote access because of underlying open architecture. An authentication scheme can verify patient's as well as TMIS server's legitimacy during remote healthcare services. To achieve security and privacy a number of authentication schemes have been proposed. Very recently Lu et al. (J. Med. Syst. 39(3):1-8, 2015) proposed a biometric based three factor authentication scheme for TMIS to confiscate the vulnerabilities of Arshad et al.'s (J. Med. Syst. 38(12):136, 2014) scheme. Further, they emphasized the robustness of their scheme against several attacks. However, in this paper we establish that Lu et al.'s scheme is vulnerable to numerous attacks including (1) Patient anonymity violation attack, (2) Patient impersonation attack, and (3) TMIS server impersonation attack. Furthermore, their scheme does not provide patient untraceability. We then, propose an improvement of Lu et al.'s scheme. We have analyzed the security of improved scheme using popular automated tool ProVerif. The proposed scheme while retaining the plusses of Lu et al.'s scheme is also robust against known attacks.

Indexed as

AlgorithmsBiometric IdentificationComputer SecurityConfidentialityHumansTelemedicineWireless TechnologyAnonymityBioHashingElliptic curve cryptographyImpersonation attackPrivacyProVerifThree factor authenticationTMIS

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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.