- Volume 9 Issue 1
DOI QR Code
User Authentication Method using EEG Signal in FIDO System
FIDO 시스템에서 EEG 신호를 이용한 사용자 인증 방법
- Kim, Yong-Ki (Department of Information & Communications, VISION College of JeonJu) ;
- Chae, Cheol-Joo (Department of General Education, Korea National College of Agriculture and Fisheries) ;
- Cho, Han-Jin (Department of Energy IT Engineering, Far East University)
- Received : 2017.11.13
- Accepted : 2018.01.20
- Published : 2018.01.28
Recently, biometric technology has begun to be used as a fusion of IT technology and financial system. Using this biometric technology, FIDO(Fast Identity Online) technology, Samsung and Apple started Samsung Pay and Apple Pay service. FIDO authentication technology replaces existing authentication methods such as passwords. Among the biometric technologies, fingerprint recognition technology is attracting attention because it can minimize the device and user rejection at a relatively low price. However, fingerprint information has a limited number of users and it can not be reused if fingerprint information is leaked by an external attacker. Therefore, in this paper, we propose a method to authenticate a user using EEG signal which is one of biometrics technologies. W propose a method to use EEG signal measurement value in FIDO system by using convenience channel by using short channel EEG device. And propose a method to utilize EEG signal when the user recognizes a specific entity by measuring the EEG signal before and after recognizing a specific entity.
Supported by : National Research Foundation of Korea(NRF)
- Sunghyun Yun, "The Biometric Authentication Scheme Capable of Multilevel Security Control," Journal of the Korea Convergence Society, Vol. 8, No. 2, pp. 9-14, 2017. https://doi.org/10.15207/JKCS.2017.8.2.009
- Sunghyun Yun, "The Biometric Authentication based Dynamic Group Signature Scheme," Journal of the Korea Convergence Society, Vol. 7, No. 1, pp. 49-55, 2016. https://doi.org/10.15207/JKCS.2016.7.1.049
- Won-Jun Jang, Hyung-Woo Lee, "Biometric One-Time Password Generation Mechanism and its Application on SIP Authentication," Journal of the Korea Convergence Society, Vol. 1, No. 1, pp. 93-100, 2010.
- Sang-Rae Cho et.al., "Passwordless Authentication Technology-FIDO," Electronics and Telecommunications Trends, 2014.
- Jaejung Kim, "Study on the password-free certification system using the FIDO (Fast IDentity Online)," Communications of the Korean Institute of Information Scientists and Engineers, Vol. 33, No. 5, pp. 9-12, 2015.
- SuHyeong Kim, "FIDO Based PinTech Authentication Technology," The Journal of The Korean Institute of Communication Sciences, Vol. 33, No. 2, pp. 59-65, 2016.
- Sangrae Cho, YoungSeob Cho, Soohyung Kim, "Overview FIDO 2.0 Authentication Technology," Korea Institute Of Information Security And Cryptology, REVIEW OF KIISC, Vol. 26, No. 2, pp. 14-19, 2016.
- Seungchul Park, "A Comparative Analysis of PKI Authentication and FIDO Authentication," Journal of the Korea Institute of Information and Communication Engineering, Vol. 21, No. 7, pp. 1411-1419, 2017. https://doi.org/10.6109/JKIICE.2017.21.7.1411
- Seungjin Han, "A Robust Mutual Authentication between User Devices and Relaying Server(FIDO Server) using Certificate Authority in FIDO Environments," Journal of the Korea Society of Computer and Information, Vol. 21, No. 10, pp. 63-68, 2016. https://doi.org/10.9708/JKSCI.2016.21.10.063
- Byoungcheon Lee, "Certified Key Management in Multi K-FIDO Device Environment," Journal of the Korea Institute of Information Security & Cryptology, Vol. 27, No. 2, pp. 293-303, 2017. https://doi.org/10.13089/JKIISC.2017.27.2.293
- Han-Gyu Ko, Jin-Man Cho, Daeseon Choi, "An Incremental Elimination Method of EEG Samples Collected by Single-Channel EEG Measurement Device for Practical Brainwave-Based User Authentication," Journal of the Korea Institute of Information Security & Cryptology, Vol. 27, No. 2, pp. 383-395, 2017. https://doi.org/10.13089/JKIISC.2017.27.2.383
- W. Khalifa, A. Salem, M. Roushdy, and K. Revett, "A Survey of EEG Based User Authentication Schemes," Proceedings of the 2012 8th International Conference on Informatics and Systems, pp. 55-60, 2012.
- David Starling, "Temporal Analysis of EEG patterns in a biofeedback based Brain Computer Interface," Tech Report No. CYB/2003/UG/DJS/1.
- G. Costantini, M. Todisco, D. Casali, M. Carota, G. Saggio, L. Bianchi, M. Abbafati and L. R. Quitadamo, "SVM Classification of EEG Signals for Brain Computer Interface," Proc. of the 2009 Confer- ence on Neural Nets WIRN09: Proceedings of the 19th Italian Workshop on Neural Networks, pp. 229-233, 2009.
- Chung-heon Lee, Jang-woo Kwon, Gyu-dong Kim, Jun-eui Hong, Dae-Seob Shin, Donghoon Lee, "A Study on EEG based Concentration Transmission and Brain Computer Interface Application," The Institute of Electronics Engineers of Korea - System and Control, Vol. 46, No. 2, pp. 41-46, 2009.
- J. Chuang, H. Nguyen, C. Wang, and B. Johnson, "I think, therefore I am: Usability and Security of Authentication using Brainwaves," Proceedings of the 2013 Workshop on Usable Security, pp. 1-16, 2013.