Publication:
Cyberattacks on miniature brain implants to disrupt spontaneous neural signaling

Simple item page
dc.contributor.authorLópez Bernal, Sergio
dc.contributor.authorFernández Maimó, Lorenzo
dc.contributor.authorTaynnan Barros, Michael
dc.contributor.authorBalasubramaniam, Sasitharan
dc.contributor.authorMartínez Pérez, Gregorio
dc.contributor.authorHuertas Celdrán, Alberto
dc.contributor.departmentIngeniería y Tecnología de Computadores
dc.contributor.otherFacultad de Informática
dc.date.accessioned2026-01-19T09:36:27Z
dc.date.available2026-01-19T09:36:27Z
dc.date.copyright© 2020 IEEE
dc.date.issued2020-08-17
dc.description.abstractBrain-Computer Interfaces (BCI) arose as systems that merge computing systems with the human brain to facilitate recording, stimulation, and inhibition of neural activity. Over the years, the development of BCI technologies has shifted towards miniaturization of devices that can be seamlessly embedded into the brain and can target single neuron or small population sensing and control. We present a motivating example highlighting vulnerabilities of two promising micron-scale BCI technologies, demonstrating the lack of security and privacy principles in existing solutions. This situation opens the door to a novel family of cyberattacks, called neuronal cyberattacks, affecting neuronal signaling. This article defines the first two neural cyberattacks, Neuronal Flooding (FLO) and Neuronal Scanning (SCA), where each threat can affect the natural activity of neurons. This work implements these attacks in a neuronal simulator to determine their impact over the spontaneous neuronal behavior, defining three metrics: number of spikes, percentage of shifts, and dispersion of spikes. Several experiments demonstrate that both cyberattacks produce a reduction of spikes compared to spontaneous behavior, generating a rise in temporal shifts and a dispersion increase. Mainly, SCA presents a higher impact than FLO in the metrics focused on the number of spikes and dispersion, where FLO is slightly more damaging, considering the percentage of shifts. Nevertheless, the intrinsic behavior of each attack generates a differentiation on how they alter neuronal signaling. FLO is adequate to generate an immediate impact on the neuronal activity, whereas SCA presents higher effectiveness for damages to the neural signaling in the long-term.
dc.formatapplication/pdf
dc.format.extent19
dc.identifier.citationIEEE Access vol. 8, 2020
dc.identifier.doihttps.//doi.org/10.1109/ACCESS.2020.3017394
dc.identifier.eissn2169-3536
dc.identifier.urihttp://hdl.handle.net/10201/188270
dc.languageeng
dc.publisherIEEE Xplore
dc.relationThis work was supported by the Irish Research Council, under the Government of Ireland Postdoctoral Fellowship under Grant GOIPD/2018/466.
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9169881
dc.rightsAttribution 4.0 International*
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectSecurity
dc.subjectArtificial neural networks
dc.subjectBiological neural networks
dc.subjectBrain computer interfaces
dc.subject.odsNo relacionado con ningún objetivo de desarrollo sostenible
dc.titleCyberattacks on miniature brain implants to disrupt spontaneous neural signaling
dc.typeinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dspace.entity.typePublicationes
relation.isAuthorOfPublicatione4351d33-87e5-4465-b4fb-6723a846fcf9
relation.isAuthorOfPublicationb8b7f907-8219-40ea-8184-f07cd22cab90
relation.isAuthorOfPublicatione4461742-104b-475f-9ca7-693d242a4d22
relation.isAuthorOfPublication155e7fdb-63ef-47a4-8068-bc025cfbabb9
relation.isAuthorOfPublication.latestForDiscoverye4351d33-87e5-4465-b4fb-6723a846fcf9
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Cyberattacks_on_Miniature_Brain_Implants_to_Disrupt_Spontaneous_Neural_Signaling.pdf
Size:
2.89 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.37 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Artículos