Evidence map›Paper›PMID 35891080›Full record

ArticleSensors (Basel, Switzerland)2022

LAP-IoHT: A Lightweight Authentication Protocol for the Internet of Health Things.

Chien-Ming Chen, Zhaoting Chen, Saru Kumari, Meng-Chang Lin

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. 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
15.3field-weighted citation impact, top 1% of its field
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, 51 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
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 at 3 institutions in 3 countries.

Chien-Ming ChenCollege of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China.ORCID 0000-0002-6502-472X
Zhaoting ChenCollege of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China.
Saru KumariDepartment of Mathematics, Chaudhary Charan Singh University, Meerut 250004, Uttar Pradesh, India.
Meng-Chang LinGraduate Institute of Nanomedicine and Medical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei 115, Taiwan.
Shandong University of Science and Technology · CNChaudhary Charan Singh University · INTaipei Medical University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Internet of Health Things (IoHT), which is an extension of the Internet of Things (IoT) in healthcare, has provided a new type of telemedicine approach. In IoHT, wearable sensors are used to collect patient health data, and information is transmitted remotely to doctors who can develop accurate treatment plans and provide timely telemedicine services to patients. However, patient health data are transmitted over a public channel, which means that the privacy and medical data of patients are at significant risk of leakage and can be confronted by serious security problems. We proposed a lightweight authentication protocol known as LAP-IoHT for IoHT environments to overcome the various threats that are currently faced by IoHT. We verified the security of LAP-IoHT using a Real-or-Random model and demonstrated its significant performance advantage by conducting a comparative analysis with other similar protocols for a better adaptation to the IoHT environment.

Indexed as

Internet of ThingsTelemedicineComputer SecurityDelivery of Health CareHumansInternetPrivacyauthenticationInternet of Health Thingsnetwork security

Identifiers

PMID35891080
PMCPMC9320153
OpenAlexW4286208748

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.