IT Subject Matter Expert, Global Service Delivery.
World Journal of Advanced Research and Reviews, 2025, 27(01), 2761-2771
Article DOI: 10.30574/wjarr.2025.27.1.2534
Received on 25 May 2025; revised on 29 August 2025; accepted on 01 September 2025
Brain-Computer Interfaces (BCIs) are developing as a promising technology in many areas, such as medical, military and consumer technology. Nevertheless, there are also serious security issues that involve the growing dependency on these technologies, especially the susceptibility to hacking. This research investigates the dangers of BCI systems and discusses the existing approaches to ensuring security of such devices against cyberattacks. The methodology will be to examine case studies in different domains, examine the literature available on vulnerabilities of BCI and to assess security practices like encryption and authentication approaches. The main conclusions include the increasing complexity of the hacking tools used to attack BCIs, and the insufficiency of the existing security systems to address the identified threats. The research highlights the necessity of sophisticated security measures and protection of neural information by advanced detection systems of threats and improved encryption to guarantee the integrity of BCI systems. The results are of critical value to researchers and developers who could use them as a basis to come up with more secure and resilient brain-computer interfaces in future.
BCI Security; Neural Data; Cybersecurity Threats; Data Encryption; Privacy Protection; Signal Manipulation; Healthcare BCIS; Real-Time Detection; Security Protocols; Neurotechnology Ethics
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Adedotun Lawrence Omotade. Neurotechnology and Human-Machine Interfaces: Securing Brain-Computer Interfaces (BCIs) Against Hacking. World Journal of Advanced Research and Reviews, 2025, 27(01), 2761-2771. Article DOI: https://doi.org/10.30574/wjarr.2025.27.1.2534.
Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0