Using a low-cost electroencephalogram (EEG) directly as random number generator

Bhanupong Petchlert; Hiroshi Hasegawa

doi:10.1109/IIAI-AAI.2014.100

Using a low-cost electroencephalogram (EEG) directly as random number generator

Bhanupong Petchlert, Hiroshi Hasegawa

Research output: Contribution to conference › Paper › peer-review

12 Citations (Scopus)

Abstract

In this paper, we propose a new encoding method for converting an electroencephalogram (EEG) signal into binary sequences which use for supplying the random numbers. We focus on low-cost EEG signal since it can be used in real applications that require true random number generator, such as gaming, gambling, and some complex model simulations. Our encoding method uses fluctuations that lie in EEG data due to noise in biometric measurements by keeping the least significant digits of real EEG sample value and then convert this value into a binary sequence. The generated binary sequences have pass most of all statistical test suite of NIST with success rate of 99.47 percent.

Original language	English
Pages	470-474
Number of pages	5
DOIs	https://doi.org/10.1109/IIAI-AAI.2014.100
Publication status	Published - 2014 Sep 29
Event	3rd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2014 - Kitakyushu, Japan Duration: 2014 Aug 31 → 2014 Sep 4

Conference

Conference	3rd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2014
Country/Territory	Japan
City	Kitakyushu
Period	14/8/31 → 14/9/4

Keywords

Biometric methods
Electroencephalogram
Random number generator

ASJC Scopus subject areas

Information Systems

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10.1109/IIAI-AAI.2014.100

Cite this

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abstract = "In this paper, we propose a new encoding method for converting an electroencephalogram (EEG) signal into binary sequences which use for supplying the random numbers. We focus on low-cost EEG signal since it can be used in real applications that require true random number generator, such as gaming, gambling, and some complex model simulations. Our encoding method uses fluctuations that lie in EEG data due to noise in biometric measurements by keeping the least significant digits of real EEG sample value and then convert this value into a binary sequence. The generated binary sequences have pass most of all statistical test suite of NIST with success rate of 99.47 percent.",

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N2 - In this paper, we propose a new encoding method for converting an electroencephalogram (EEG) signal into binary sequences which use for supplying the random numbers. We focus on low-cost EEG signal since it can be used in real applications that require true random number generator, such as gaming, gambling, and some complex model simulations. Our encoding method uses fluctuations that lie in EEG data due to noise in biometric measurements by keeping the least significant digits of real EEG sample value and then convert this value into a binary sequence. The generated binary sequences have pass most of all statistical test suite of NIST with success rate of 99.47 percent.

AB - In this paper, we propose a new encoding method for converting an electroencephalogram (EEG) signal into binary sequences which use for supplying the random numbers. We focus on low-cost EEG signal since it can be used in real applications that require true random number generator, such as gaming, gambling, and some complex model simulations. Our encoding method uses fluctuations that lie in EEG data due to noise in biometric measurements by keeping the least significant digits of real EEG sample value and then convert this value into a binary sequence. The generated binary sequences have pass most of all statistical test suite of NIST with success rate of 99.47 percent.

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KW - Electroencephalogram

KW - Random number generator

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T2 - 3rd IIAI International Conference on Advanced Applied Informatics, IIAI-AAI 2014

Y2 - 31 August 2014 through 4 September 2014

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Using a low-cost electroencephalogram (EEG) directly as random number generator

Abstract

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Keywords

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