Evidence map›Paper›PMID 33265185›Full record

ArticleEntropy (Basel, Switzerland)2018

Heartbeats Do Not Make Good Pseudo-Random Number Generators: An Analysis of the Randomness of Inter-Pulse Intervals.

Lara Ortiz-Martin, Pablo Picazo-Sanchez, Pedro Peris-Lopez, Juan Tapiador

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Article in Entropy (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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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.

Lara Ortiz-MartinDepartment of Computer Science, Carlos III University of Madrid, 28911 Leganés, Spain.
Pablo Picazo-SanchezDepartment of Computer Science and Engineering, Chalmers University of Technology∣Gothenburg University, 41296 Gothenburg, Sweden.ORCID 0000-0002-0303-3858
Pedro Peris-LopezDepartment of Computer Science, Carlos III University of Madrid, 28911 Leganés, Spain.ORCID 0000-0001-6943-0760
Juan TapiadorDepartment of Computer Science, Carlos III University of Madrid, 28911 Leganés, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The proliferation of wearable and implantable medical devices has given rise to an interest in developing security schemes suitable for these systems and the environment in which they operate. One area that has received much attention lately is the use of (human) biological signals as the basis for biometric authentication, identification and the generation of cryptographic keys. The heart signal (e.g., as recorded in an electrocardiogram) has been used by several researchers in the last few years. Specifically, the so-called Inter-Pulse Intervals (IPIs), which is the time between two consecutive heartbeats, have been repeatedly pointed out as a potentially good source of entropy and are at the core of various recent authentication protocols. In this work, we report the results of a large-scale statistical study to determine whether such an assumption is (or not) upheld. For this, we have analyzed 19 public datasets of heart signals from the Physionet repository, spanning electrocardiograms from 1353 subjects sampled at different frequencies and with lengths that vary between a few minutes and several hours. We believe this is the largest dataset on this topic analyzed in the literature. We have then applied a standard battery of randomness tests to the extracted IPIs. Under the algorithms described in this paper and after analyzing these 19 public ECG datasets, our results raise doubts about the use of IPI values as a good source of randomness for cryptographic purposes. This has repercussions both in the security of some of the protocols proposed up to now and also in the design of future IPI-based schemes.

Indexed as

authenticationbiometricimplantable medical devicesinter-pulse intervalsprivacyrandomness

Identifiers

PMID33265185
PMCPMC7512659

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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.