Electrocardiogram signals-based user authentication systems using soft computing techniques

被引:13
作者
Hosseinzadeh, Mehdi [1 ,2 ]
Vo, Bay [3 ]
Ghafour, Marwan Yassin [5 ]
Naghipour, Sajjad [4 ]
机构
[1] Duy Tan Univ, Inst Res & Dev, Da Nang 550000, Vietnam
[2] Iran Univ Med Sci, Hlth Management & Econ Res Ctr, Tehran, Iran
[3] Ho Chi Minh City Univ Technol HUTECH, Fac Informat Technol, Ho Chi Minh City, Vietnam
[4] Afagh Higher Educ Inst, Comp Engn Dept, Orumiyeh, Iran
[5] Univ Halabja, Coll Sci, Dept Comp Sci, Halabja, Iraq
关键词
ECG; Authentication; Security; Feature selection; SVM; CNN; Deep learning; BIOMETRIC AUTHENTICATION; ECG AUTHENTICATION; EXISTING AUTHENTICATION; NEURAL-NETWORK; MOBILE; FUSION; FINGERPRINT; SECURITY; INTERNET; SCHEMES;
D O I
10.1007/s10462-020-09863-0
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
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.
引用
收藏
页码:667 / 709
页数:43
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