Security Issues in Brain – Computer Interfaces (BCI)

Introduction: Brain-computer interface (BCI) systems emerged to harness and interpret the electrical activity of the brain for interaction with external devices. BCI, or Brain-Machine Interface (BMI), integrates hardware and software to facilitate human-environment interaction, independently of peripheral nerves and muscles, through control signals from electroencephalographic data. However, in the area of ​​security, BCI systems remain underdeveloped. The importance of security in BCI systems has only recently attracted attention, leading to the emergence of terms such as neurosecurity and neuroethics. The literature has identified categories of security threats that affect the integrity and confidentiality of BCI, however, comprehensive research on these issues is still lacking. Purpose: The purpose of this literature review is to describe the potential security attacks that affect each phase of the life cycle of a BCI system. Also, the analysis of the impacts of these attacks as well as the possible countermeasures that can be used and how they are documented based on the international literature. Material and Method: A narrative literature review was conducted based on articles from scientific databases (PubMed /Medline, Google Scholar) using specific keywords in Greek and English, in printed books and online references. Results: A critical review of the literature reveals that the security field focused on BCI system technologies is not yet mature, creating opportunities for malicious actors to launch attacks. Even unsophisticated attacks can however have a significant impact on both BCI system technologies and user security. In addition, the development of standardization initiatives for the unification of BCI systems in terms of information is recognized as an opportunity. Well-studied areas such as implantable medical devices and the Internet of Things can provide guidance for the development of robust security mechanisms, while user awareness of security issues in BCI systems is considered crucial. Conclusions: Significant advances in BCI research have occurred over the past two decades, leveraging established methodologies in signal processing and pattern recognition. Many studies have improved the accuracy of BCI and proposed methods for efficient information transfer, despite challenges in brain signal processing. As a result, user training time has been reduced, facilitating broader application of BCI for people with disabilities, including word processing and neuroprosthetics. Most BCI applications are still in the research phase and are not yet suitable for widespread everyday use. Current limitations include low information transfer rates, variable reliability, and inconvenience due to electrode maintenance requirements and software handling. There are many proposed countermeasures to mitigate risks, but extensive research is still necessary, due to the significant threats associated with these systems.