Electrocardiogram signals-based user authentication systems using soft computing techniques
作者:Mehdi Hosseinzadeh, Bay Vo, Marwan Yassin Ghafour, Sajjad Naghipour
摘要
With the advent of various security attacks, biometric authentication methods are gaining momentum in the security literature. Electrocardiogram or ECG signals are one of the essential biometric features generated by the human heart’s electrical activities. Many authentication schemes apply these signals due to their uniqueness, resistance to fabrication attacks, and support for continuous authentication. This survey article focuses on the ECG-based authentication approaches and provides the required background knowledge about the ECG signals and authentication methods. Then, it presents a taxonomy of the ECG-based authentication approaches first based on the authentication factors and then according to the applied algorithms for conducting authentication. It then describes their key contributions, applied algorithms, and possible drawbacks. Furthermore, their employed evaluation factors, ECG datasets, and simulators are illuminated and compared. Finally, the concluding remarks and future studies directions in this context are provided.
论文关键词:ECG, Authentication, Security, Feature selection, SVM, CNN, Deep learning
论文评审过程:
论文官网地址:https://doi.org/10.1007/s10462-020-09863-0