Threat Vectors and the State of the Art in Defense Methods for Security in Neurotechnology
2026-07-11 • Cryptography and Security
Cryptography and SecurityEmerging TechnologiesHuman-Computer Interaction
AI summaryⓘ
The authors explain that brain-computer interfaces (BCIs) are devices that connect the brain to computers and are used in areas like medicine and brain research. While BCI technology has advanced quickly and some devices are now available or close to use, the security measures to protect these systems have not kept up. The paper reviews the current security risks linked to BCIs and suggests ways to use existing cybersecurity and hardware protection methods to improve safety right away. The authors aim to help address vulnerabilities in BCI technology before they cause harm.
Brain-Computer InterfaceNeurosecurityCybersecurityHardware SecurityNeurotechnologyClinical TrialsBiomedical Data AnalysisMachine LearningNeuroimaging
Authors
Bryce-Allen Bagley, Nathaniel Rose, Quintus Kilbourn, Matthew Canham
Abstract
Brain-computer interfaces (BCIs) are a class of diverse hardware modalities, associated software, and connected devices which are widely used in a variety of fields, including neurosurgery, biomedical data analysis, and neuroimaging. Recent years have seen rapid advancements in BCI technology, and neurotechnology more broadly, with the first devices now passing clinical trials, early examples of consumer hardware entering the market, and many variants of consumer and medical hardware with increasingly extensive capabilities being developed rapidly. However, research and development in security for BCIs--known as neurosecurity--lags significantly behind the capabilities of BCIs themselves. In an effort to address as many vulnerabilities as feasible immediately, in this paper we review the current state of the art in neurosecurity, thoroughly survey the breadth and complexity of both firmly established and highly probable security threats to BCI systems, and provide recommendations of existing methods from cybersecurity, hardware security, and machine learning which can immediately be applied to address some of these gaps in neurosecurity.