Evidence map›Paper›PMID 37296171›Full record

ArticleScientific reports2023

A memristor fingerprinting and characterisation methodology for hardware security.

Callum Aitchison, Basel Halak, Alex Serb, Themis Prodromakis

Abstract read
In one paragraph

Article in Scientific reports, 2023. 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

4 authors.

Callum AitchisonElectronics and Computer Science, University of Southampton, University Road, Southampton, SO17 1BJ, UK. callum.aitchison@soton.ac.uk.
Basel HalakElectronics and Computer Science, University of Southampton, University Road, Southampton, SO17 1BJ, UK.
Alex SerbCentre for Electronics Frontiers, Institute for Integrated Micro and Nano Systems, School of Engineering, The University of Edinburgh, Edinburgh, UK.
Themis ProdromakisCentre for Electronics Frontiers, Institute for Integrated Micro and Nano Systems, School of Engineering, The University of Edinburgh, Edinburgh, UK.

Funding

Royal Academy of Engineering CiET1819/2/93Royal Academy of Engineering IF2021\36UK Research and Innovation EP/R007268/1UK Research and Innovation EP/R024642/1UK Research and Innovation EP/S024298/1
6 · The paper itself

Abstract

The modern IC supply chain encompasses a large number of steps and manufacturers. In many applications it is critically important that chips are of the right quality and are assured to have been obtained from the legitimate supply chain. To this end, it is necessary to be able to uniquely identify systems to aid in supply chain tracking and quality assurance. Many identifiers, however, can be cloned onto counterfeit devices and are therefore untrustworthy. This paper proposes a methodology for using post-CMOS memristor devices as a fingerprint to uniquely identify ICs. To achieve this, memristors' unique and variable I-V characteristics are exploited to produce a fingerprint that can be generally applicable to a wide variety of different memristor technologies and identifiable over time, even where cell retention is non-ideal. In doing so it aims to minimise the hardware required on-chip both to minimise cost and maximise the auditability of the system. The methodology is applied to a [Formula: see text] memristor technology, and shown to be able to identify cells in a set.

Indexed as

Neural Networks, ComputerSynapsesComputersFood, FormulatedTechnology

Identifiers

PMID37296171
PMCPMC10256690

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.