Evidence map›Paper›PMID 31213619›Full record

ArticleScientific reports2019

Genetic similarity of biological samples to counter bio-hacking of DNA-sequencing functionality.

Mohd Siblee Islam, Stepan Ivanov, Eric Robson, Tríona Dooley-Cullinane, Lee Coffey, Kevin Doolin, Sasitharan Balasubramaniam

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

7 authors.

Mohd Siblee IslamMcAfee Ireland Ltd., Building 2000, City Gate, Mahon, Cork, Ireland.
Stepan IvanovTelecommunications Software and Systems Group, Waterford Institute of Technology, Waterford, Ireland. sivanov@tssg.org.ORCID http://orcid.org/0000-0001-7548-8408
Eric RobsonTelecommunications Software and Systems Group, Waterford Institute of Technology, Waterford, Ireland.
Tríona Dooley-CullinanePharmaceutical and Molecular Biotechnology Research Centre, Waterford Institute of Technology, Waterford, Ireland.
Lee CoffeyPharmaceutical and Molecular Biotechnology Research Centre, Waterford Institute of Technology, Waterford, Ireland.
Kevin DoolinTelecommunications Software and Systems Group, Waterford Institute of Technology, Waterford, Ireland.
Sasitharan BalasubramaniamTelecommunications Software and Systems Group, Waterford Institute of Technology, Waterford, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present the work towards strengthening the security of DNA-sequencing functionality of future bioinformatics systems against bio-computing attacks. Recent research has shown how using common tools, a perpetrator can synthesize biological material, which upon DNA-analysis opens a cyber-backdoor for the perpetrator to hijack control of a computational resource from the DNA-sequencing pipeline. As DNA analysis finds its way into practical everyday applications, the threat of bio-hacking increases. Our wetlab experiments establish that malicious DNA can be synthesized and inserted into E. coli, a common contaminant. Based on that, we propose a new attack, where a hacker to reach the target hides the DNA with malicious code on common surfaces (e.g., lab coat, bench, rubber glove). We demonstrated that the threat of bio-hacking can be mitigated using dedicated input control techniques similar to those used to counter conventional injection attacks. This article proposes to use genetic similarity of biological samples to identify material that has been generated for bio-hacking. We considered freely available genetic data from 506 mammary, lymphocyte and erythrocyte samples that have a bio-hacking code inserted. During the evaluation we were able to detect up to 95% of malicious DNAs confirming suitability of our method.

Indexed as

Base SequenceBiometric IdentificationComputational BiologyComputer SecurityDNAErythrocytesEscherichia coliGenetic VariationHumansInformation Storage and RetrievalLymphocytesRisk AssessmentRisk FactorsSequence Analysis, DNADNA

Identifiers

PMID31213619
PMCPMC6581904

What OpenQuestion holds

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Registered trials

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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.