survey

Mind Your Mind: EEG-Based Brain-Computer Interfaces and Their Security in Cyber Space

Authors:

Nir NissimAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 53, Issue 1

Article No.: 17, Pages 1 - 38

https://doi.org/10.1145/3372043

Published: 06 February 2020 Publication History

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.

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Index Terms

Mind Your Mind: EEG-Based Brain-Computer Interfaces and Their Security in Cyber Space
1. Security and privacy
  1. Human and societal aspects of security and privacy

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 53, Issue 1

January 2021

781 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3382040

Editor:
Albert Zomaya
University of Sydney, Australia

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Publication History

Published: 06 February 2020

Accepted: 01 November 2019

Revised: 01 November 2019

Received: 01 June 2019

Published in CSUR Volume 53, Issue 1

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https://doi.org/10.1016/B978-0-443-33414-6.00014-9
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