A data security scheme based on EEG characteristics for body area networks

Tong Bai; Yuhao Jiang; Jiazhang Yang; Jiasai Luo; Ya Du

doi:10.3389/fnins.2023.1174096

A data security scheme based on EEG characteristics for body area networks

Front Neurosci. 2023 May 18:17:1174096. doi: 10.3389/fnins.2023.1174096. eCollection 2023.

Authors

Tong Bai^#¹, Yuhao Jiang^#¹, Jiazhang Yang², Jiasai Luo¹, Ya Du³

Affiliations

¹ School of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China.
² The Women and Children Hospital of Yongchuan, Chongqing, China.
³ Department of Peripheral Vascular (Wound Repair), Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China.

^# Contributed equally.

Abstract

Body area network (BAN) is a body-centered network of wireless wearable devices. As the basic technology of telemedicine service, BAN has aroused an immense interest in academia and the industry and provides a new technical method to solve the problems that exist in the field of medicine. However, guaranteeing full proof security of BAN during practical applications has become a technical issue that hinders the further development of BAN technology. In this article, we propose a data encryption method based on electroencephalogram (EEG) characteristic values and linear feedback shift register (LFSR) to solve the problem of data security in BAN. First, the characteristics of human EEG signals were extracted based on the wavelet packet transform method and as the MD5 input data to ensure its randomness. Then, an LFSR stream key generator was adopted. The 128-bit initial key obtained through the message-digest algorithm 5 (MD5) was used to generate the stream key for BAN data encryption. Finally, the effectiveness of the proposed security scheme was verified by various experimental evaluations. The experimental results showed that the correlation coefficient of data before and after encryption was very low, and it was difficult for the attacker to obtain the statistical features of the plaintext. Therefore, the EEG-based security scheme proposed in this article presents the advantages of high randomness and low computational complexity for BAN systems.

Keywords: body area network; data security; electroencephalogram; linear feedback shift register; wavelet packet transform.

Grants and funding

The project was funded by the National Natural Science Foundation of China (62171073, 61971079, and U21A20447), the Department of Science and Technology of Sichuan Province (2020YFQ0025 and 2020YJ0151), the Project of Central Nervous System Drug Key Laboratory of Sichuan Province (210022-01SZ, 200020-01SZ, 200028-01SZ, and 200027-01SZ), the Nature Science Foundation of Chongqing (cstc2019jcyj-msxmX0275, cstc2020jcyj-cxttX0002, cstc2019jcyjmsxmX0666, cstc2021jscx-gksbx0051, and cstc2021jcyj-bsh0221), the Science and Technology Research Project of Chongqing Municipal Education Commission (KJZD-k202000604, KJQN202100602, KJQN202100602, and KJQN202000604), the Key Research Project of Southwest Medical University (2021ZKZD019), the special support for the Chongqing Postdoctoral Research Project (2021XM3010 and 2021XM2051), and the Project funded by the China Postdoctoral Science Foundation (2022MD713702, 2021MD703941, and 2021M693931).