Merging brain computing interface (BCI) & neural networks for better authentication & recognition

3rd International Conference "Cognitive Robotics"

计算机科学

Ramzan, Q.^1^2 ; Syryamkin, V.I.^1

National Research Tomsk State University, Tomsk, Russia^1

ToggleTechs (A Creativity Platform), Islamabad, Pakistan^2

关键词: Authentication methods;    Authentication models;    Authentication systems;    Brain computing;    EEG signals;    Its efficiencies;    Security protocols;    Self-learning;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/516/1/012041/pdf
DOI  :  10.1088/1757-899X/516/1/012041

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Brain Computing Interface (BCI) has been proved helpful for the different streams of technology, considering the sensitivity of data in the current era it is required to build new security protocols and authentication models. Just like other fields of technology Brain Computing Interface could also be useful for making the data security better by using BCI as an authentication method without any hard physical inputs. The focus of the issue shifts to 'recognition' of EEG signals pattern and making the authentication model self-learning to increase its efficiency. This leads us to involve Artificial Neural Networks in the authentication system to make it efficient and intelligent.