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Authentication System by Human Brainwaves Using Machine Learning and Artificial Intelligence

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Advances in Computer Science for Engineering and Education IV (ICCSEEA 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 83))

Abstract

Authentication and authorization are an indispensable piece of security in computer-based frameworks. As an option for biometrics, electroencephalography (EEG) authentication (authorization) presents focal points contrasted with other biological qualities. Brainwaves are difficult to reproduce, and diverse mental undertakings produce various brainwaves. This examination researches the parts of execution and time-invariance of the EEG-based confirmation. Two arrangements of trials are done to record EEG of various people. We actualize the utilization of artificial intelligence (AI), for example, support vector machine (SVM) and deep neural network (DNN) to characterize EEG of subjects. The correlation between EEG highlights, anodes position, and a mental errand is made. We accomplish more than 90% order exactness utilizing three kinds of highlights from four electrodes. Information from prior meetings is utilized as AI preparing information and information from later meeting are grouped. We discovered that characterization precision diminishes after some time, and inactive undertakings perform in a way that is better than dynamic errands.

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Acknowledgments

This scientific work was partially supported by RAMECS and self-determined research funds of CCNU from the colleges’ primary research and operation of MOE (CCNU19TS022).

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Authors and Affiliations

  1. National Aviation University, Kyiv, Ukraine

    Z. B. Hu

  2. Borys Grinchenko Kyiv University, Kyiv, Ukraine

    V. Buriachok, M. TajDini & V. Sokolov

Authors
  1. Z. B. Hu
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  2. V. Buriachok
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  3. M. TajDini
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  4. V. Sokolov
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Corresponding author

Correspondence to V. Sokolov .

Editor information

Editors and Affiliations

  1. School of Educational Information Technology, Central China Normal University, Wuhan, China

    Zhengbing Hu

  2. Mechanical Engineering Research Institute of the Russian Academy of Sciences, Moscow, Russia

    Sergey Petoukhov

  3. Faculty of Applied Mathematics, National Technical University of Ukraine “Igor Sikorsky Kiev Polytechnic Institute”, Kiev, Ukraine

    Ivan Dychka

  4. Halmos College of Natural Sciences and Oceanography, Nova Southeastern University, Plantation, FL, USA

    Matthew He

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Hu, Z.B., Buriachok, V., TajDini, M., Sokolov, V. (2021). Authentication System by Human Brainwaves Using Machine Learning and Artificial Intelligence. In: Hu, Z., Petoukhov, S., Dychka, I., He, M. (eds) Advances in Computer Science for Engineering and Education IV. ICCSEEA 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 83. Springer, Cham. https://doi.org/10.1007/978-3-030-80472-5_31

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