ECG Security Challenges: Case Study on Change of ECG According to Time for User Identification
Each person has unique bio-information such as: a face, a fingerprint, an iris, which are forms of static information and many systems have been trying to use them in their security systems, like a banking system. However, because they are just static information, which are never changing, they could be abused by replacing them with an attacker’s bio-information. To overcome this, dynamic bio-information, such as an Electrocardiogram (ECG), can be used in the next forms of security systems. One problem is that the dynamic bio-information is always different according to their state of health, evaluating time, moreover, their daily condition when they are evaluated. Therefore the security system can’t accept and pass with two different values. So, to use the ECG value in the security system, it tries to detect the ECG’s feature and tries to connect each relationship.
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2018R1D1A1B07040679). This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education (No. 2017R1A6A1A03015496).
- 1.C. Chan, S. Ginosar, T. Zhou, and A. A. Efros, “Everybody dance now,“arXiv preprint arXiv:1808.07371, 2018.Google Scholar
- 2.S. I. Safie, J. J. Soraghan, and L. Petropoulakis, “Ecg based biometric for doubly secure authentication,” in Signal Processing Conference, 2011 19th European. IEEE, 2011, pp. 2274–2278.Google Scholar
- 4.F. Gargiulo, A. Fratini, M. Sansone, and C. Sansone, “Subject identification via ecg fiducial-based systems: Influence of the type of qt interval correction,” Computer methods and programs in biomedicine, vol. 121, no. 3, pp. 127–136, 2015.Google Scholar
- 5.T. N. Gia, M. Jiang, A.-M. Rahmani, T. Westerlund, P. Liljeberg, and H. Tenhunen, “Fog computing in healthcare internet of things: A case study on ecg feature extraction,” in Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (CIT/IUCC/DASC/PICOM), 2015 IEEE International Conference on. IEEE, 2015, pp. 356–363.Google Scholar
- 6.T. T. Khan, N. Sultana, R. B. Reza, and R. Mostafa, “Ecg feature extraction in temporal domain and detection of various heart conditions,” in Electrical Engineering and Information Communication Technology (ICEEICT), 2015 International Conference on. IEEE, 2015, pp.1–6.Google Scholar