Cyber Risks to Next-Gen Brain-Computer Interfaces: Analysis and Recommendations
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866913996014092288 |
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| author | Schroder, Tyler Sirbu, Renee Park, Sohee Morley, Jessica Street, Sam Floridi, Luciano |
| author_facet | Schroder, Tyler Sirbu, Renee Park, Sohee Morley, Jessica Street, Sam Floridi, Luciano |
| contents | Brain-computer interfaces (BCIs) show enormous potential for advancing personalized medicine. However, BCIs also introduce new avenues for cyber-attacks or security compromises. In this article, we analyze the problem and make recommendations for device manufacturers to better secure devices and to help regulators understand where more guidance is needed to protect patient safety and data confidentiality. Device manufacturers should implement the prior suggestions in their BCI products. These recommendations help protect BCI users from undue risks, including compromised personal health and genetic information, unintended BCI-mediated movement, and many other cybersecurity breaches. Regulators should mandate non-surgical device update methods, strong authentication and authorization schemes for BCI software modifications, encryption of data moving to and from the brain, and minimize network connectivity where possible. We also design a hypothetical, average-case threat model that identifies possible cybersecurity threats to BCI patients and predicts the likeliness of risk for each category of threat. BCIs are at less risk of physical compromise or attack, but are vulnerable to remote attack; we focus on possible threats via network paths to BCIs and suggest technical controls to limit network connections. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_12571 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Cyber Risks to Next-Gen Brain-Computer Interfaces: Analysis and Recommendations Schroder, Tyler Sirbu, Renee Park, Sohee Morley, Jessica Street, Sam Floridi, Luciano Cryptography and Security Computers and Society Emerging Technologies Human-Computer Interaction Neural and Evolutionary Computing Brain-computer interfaces (BCIs) show enormous potential for advancing personalized medicine. However, BCIs also introduce new avenues for cyber-attacks or security compromises. In this article, we analyze the problem and make recommendations for device manufacturers to better secure devices and to help regulators understand where more guidance is needed to protect patient safety and data confidentiality. Device manufacturers should implement the prior suggestions in their BCI products. These recommendations help protect BCI users from undue risks, including compromised personal health and genetic information, unintended BCI-mediated movement, and many other cybersecurity breaches. Regulators should mandate non-surgical device update methods, strong authentication and authorization schemes for BCI software modifications, encryption of data moving to and from the brain, and minimize network connectivity where possible. We also design a hypothetical, average-case threat model that identifies possible cybersecurity threats to BCI patients and predicts the likeliness of risk for each category of threat. BCIs are at less risk of physical compromise or attack, but are vulnerable to remote attack; we focus on possible threats via network paths to BCIs and suggest technical controls to limit network connections. |
| title | Cyber Risks to Next-Gen Brain-Computer Interfaces: Analysis and Recommendations |
| topic | Cryptography and Security Computers and Society Emerging Technologies Human-Computer Interaction Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2508.12571 |