Evidence map›Paper›PMID 31052275›Full record

ArticleSensors (Basel, Switzerland)2019

Design and Analysis of a True Random Number Generator Based on GSR Signals for Body Sensor Networks.

Carmen Camara, Honorio Martín, Pedro Peris-Lopez, Muawya Aldalaien

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. 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
4.6field-weighted citation impact, top 5% 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

1 citing paper in PubMed, 18 citations in OpenAlex.

  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

4 authors at 2 institutions in 2 countries.

Carmen CamaraDepartment of Computer Science, University Carlos III of Madrid, 28911 Leganes, Spain. macamara@pa.uc3m.es.
Honorio MartínDepartment of Electronic Technology, University Carlos III of Madrid, 28911 Leganes, Spain. hmartin@ing.uc3m.es.ORCID 0000-0002-8720-406X
Pedro Peris-LopezDepartment of Computer Science, University Carlos III of Madrid, 28911 Leganes, Spain. pperis@inf.uc3m.es.ORCID 0000-0001-6943-0760
Muawya AldalaienHigher Colleges of Technology, Abu Dhabi Women's College, Abu Dhabi 41012, United Arab Emirates. maldalaien@hct.ac.ae.ORCID 0000-0002-1407-652X
Universidad Carlos III de Madrid · ESHigher Colleges of Technology · AE

Funding

Comunidad de Madrid P2018/TCS-4566Interdisciplinary Research Funds (HTC, United Arab Emirates) Nr. 103104Ministerio de Economía, Industria y Competitividad, Gobierno de España ESP-2015-68245-C4-1-PMinisterio de Economía, Industria y Competitividad, Gobierno de España TIN2016-79095-C2-2-R
6 · The paper itself

Abstract

Today, medical equipment or general-purpose devices such as smart-watches or smart-textiles can acquire a person's vital signs. Regardless of the type of device and its purpose, they are all equipped with one or more sensors and often have wireless connectivity. Due to the transmission of sensitive data through the insecure radio channel and the need to ensure exclusive access to authorised entities, security mechanisms and cryptographic primitives must be incorporated onboard these devices. Random number generators are one such necessary cryptographic primitive. Motivated by this, we propose a True Random Number Generator (TRNG) that makes use of the GSR signal measured by a sensor on the body. After an exhaustive analysis of both the entropy source and the randomness of the output, we can conclude that the output generated by the proposed TRNG behaves as that produced by a random variable. Besides, and in comparison with the previous proposals, the performance offered is much higher than that of the earlier works.

Indexed as

entropyGalvanic Skin Response (GSR)Hilbert transformrandomnessRandom Number Generators (RNG)

Identifiers

PMID31052275
PMCPMC6540050
OpenAlexW2943014868

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.