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The EEG signals encryption algorithm with K-sine-transform-based coupling chaotic system.

Authors :
Wen, Dong
Jiao, Wenlong
Li, Xiaoling
Wan, Xianglong
Zhou, Yanhong
Dong, Xianling
Lan, Xifa
Han, Wei
Source :
Information Sciences. Apr2023, Vol. 622, p962-984. 23p.
Publication Year :
2023

Abstract

Telemedicine provides remote online services for digital diagnosis and treatment via the Internet. However, there is a risk of data leakage during transmission. Therefore, data protection is an important challenge for telemedicine. Chaos is widely used in image, audio, and EEG encryption because of its unique characteristics of unpredictability, nonlinearity, and sensitivity to an initial state. However, some chaotic maps have various security issues. To solve these problems, this paper proposes a K-sine-transform-based coupled chaotic system (K-STBCCS), combining any two one-dimensional chaotic mappings to generate a new chaos mapping. To demonstrate the reliability of the system, this paper generates three new chaotic mappings using K-STBCCS and analyzes their performance. Using the chaotic mapping generated by K-STBCCS, this paper further proposes an EEG signal encryption scheme based on the confusion-diffusion principle. The purpose of confusion is to separate adjacent EEG signals, while the purpose of diffusion is to change the value of EEG signals. Among them, the diffusion operation uses positive and negative diffusion to reduce the correlation between the ciphertext and the original signals. The experimental results and security analysis show that the proposed EEG signal encryption scheme performs well and passes the rigorous cryptographic security test. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00200255
Volume :
622
Database :
Academic Search Index
Journal :
Information Sciences
Publication Type :
Periodical
Accession number :
161816985
Full Text :
https://doi.org/10.1016/j.ins.2022.12.001