Show simple item record

dc.contributor.authorArmengol-Urpi, Alexandre
dc.contributor.authorKovacs, Reid
dc.contributor.authorSarma, Sanjay
dc.date.accessioned2023-12-13T17:20:23Z
dc.date.available2023-12-13T17:20:23Z
dc.date.issued2023-11-26
dc.identifier.isbn979-8-4007-0254-9
dc.identifier.urihttps://hdl.handle.net/1721.1/153146
dc.description.abstractThe promise of Brain-Computer Interfaces (BCIs) is counterbalanced by concerns about vulnerabilities. Recent studies have revealed that EEG-based BCIs are susceptible to security breaches. However, current attack approaches are challenging to execute in real-world settings because they need access to, at a minimum, the EEG data stream. In this work, we introduce an unexplored vulnerability of current EEG-based BCIs that consists of remotely injecting false brain-waves into the recording device. We do this by transmitting amplitude-modulated radio-frequency (RF) signals that are received by the physical structure of the EEG equipment. We demonstrate the versatility of our system by successfully attacking three different categories of EEG devices: research-grade (Neuroelectrics), open-source (OpenBCI), and consumer-grade (Muse). We test our attack system by taking control of three different BCIs: a virtual keyboard speller, a drone-control interface, and a neuro-feedback meditation interface. Our system was successful in each case, forcing the input of any desired character with the virtual keyboard, crashing the drone, and reporting false meditative states, respectively. To the best of our knowledge, this is the first time that an EEG device is remotely hacked at the physical layer. This work shows the risks that can arise from this type of attacks, which can not only be dangerous by seizing control of a BCI, but could also lead to severe misdiagnoses in clinical EEG tests.en_US
dc.publisherACM|Proceedings of the 5th Workshop on CPS&IoT Security and Privacyen_US
dc.relation.isversionofhttps://doi.org/10.1145/3605758.3623497en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceAssociation for Computing Machineryen_US
dc.titleBrain-Hack: Remotely Injecting False Brain-Waves with RF to Take Control of a Brain-Computer Interfaceen_US
dc.typeArticleen_US
dc.identifier.citationArmengol-Urpi, Alexandre, Kovacs, Reid and Sarma, Sanjay. 2023. "Brain-Hack: Remotely Injecting False Brain-Waves with RF to Take Control of a Brain-Computer Interface."
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.identifier.mitlicensePUBLISHER_CC
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2023-12-01T08:48:32Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2023-12-01T08:48:32Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record