Mind Your Mind

Abstract

A brain-computer interface (BCI) system is a system that leverages brainwave information acquired by a designated brain monitoring device to interact with a computerized system. Over the past 40 years, many BCI applications have been developed in a variety of domains, from entertainment to medical field and even to computer security mechanisms. Until now, the development of BCI systems has focused on improving their accuracy, functionality, and ease of use, and not enough effort and attention has been invested in securing these systems and the sensitive data they acquire. In this article, we present the principles of brain activity data acquisition, with a special focus on EEG, and we present a taxonomy of BCI applications and domains. We also provide a comprehensive survey that covers eight possible attacks aimed at BCI systems. For each BCI application, we created an ecosystem and data and attack flow-diagram, which comprehensively describes the roles and interactions of the players associated with the BCI application and presents the most vulnerable vectors and components within its ecosystem; we identified gaps between existing security solutions and the presented attacks and vulnerabilities. Finally, we provide several concrete suggestions for improving the security of BCI systems in cyber-space.

Brain-Computer Interface Integration With Extended Reality (XR): Future, Privacy And Security Outlook

“…Privacy and security must be ensured by keeping the firmware/software updated and adding various anti-virus/malware detection programs or data traffic management to prevent unauthorized system use (Lahtinen & Costin 2023). As Landau et al (2020) and O'Hagan et al ( 2023) suggest, it is important to keep unauthorized people away from the BCIs, and authorized people should only have minimal privileges (Tabasum et al 2018). This can be done by establishing access control policies, for example, by defining who has access to raw data (O'Hagan et al 2023).…”

“…The captured data can contain sensitive brain data and this data could legitimately be used to diagnose Alzheimer's disease, possibly other diseases, or sensitive information about the BCI user. It is important to understand that data leakage can occur in any part of the BCI system (Landau et al 2020).…”

The functional differentiation of brain–computer interfaces (BCIs) and its ethical implications

“…Users' privacy security could be seriously threatened when attackers misuse the private information generated by users' brains and predict their mental activities, intentions, beliefs, health information, and personality traits (Inzlicht et al, 2009;Chaudhary and Agrawal, 2018). Landau et al (2020aLandau et al ( , 2020b illustrated that the collection of EEG data via BCI applications constitutes an encroachment upon privacy. Furthermore, they established that personality traits can be deduced from this EEG data.…”

“…In a concerning scenario, if malicious actors were to gain access to both the EEG scan data from the gaming environment and hospital records, they could conduct comparative analyses to extract intricate user details. This, in turn, has the potential to result in discriminatory practices against specific populations, with implications for fairness (Landau et al, 2020a(Landau et al, , 2020b.…”

Distraction descriptor for brainprint authentication modelling using probability-based Incremental Fuzzy-Rough Nearest Neighbour

“…EEG signals are usually nonlinear, nonstationary, and difficult to recreate due to the impact of several noise sources such as environmental noise and physiological noise [ 5 , 11 ]. Current research normally conducted the EEG recording in a very quiet environment to minimize the disturbance [ 12 , 13 ]. However, these environments are highly artificial and significantly differ from real-world situations, where people have to handle the environmental distractions.…”