Research on Privacy Preserving ECG-based Identification Technology

doi:10.3969/j.issn.1671-1122.2016.08.001

Abstract

Abstract:

ECG data are physiological characteristics that are closely related to an individual, which has an unparalleled advantage for authentication. However, ECG data reflect the health situation of an individual, which belong to the important personal privacy. This paper proposes a privacy preserving ECG-based identification technology. Firstly, a certain mechanism is adopted to protect the ECG data in the data training phase and the data matching phase, and then identification experiments on the protected ECG data are conducted by the Euclidean distance algorithm and the cross-correlation algorithm. The results show that the ECG data in MIT-BIH Normal Sinus Rhythm Database are 100% identified by the Euclidean distance algorithm and the cross-correlation algorithm, and the ECG data in MIT-BIH Arrhythmia Database are 96.77% identified by the Euclidean distance algorithm and the cross-correlation algorithm.

Key words: privacy protection, ECG, identification, Euclidean distance, cross-correlation

CLC Number:

TP309

Shaopeng GUAN, Xin GE, Yuan ZHANG, Sheng ZHONG. Research on Privacy Preserving ECG-based Identification Technology[J]. Netinfo Security, 2016, 16(8): 1-5.

Figures/Tables 5

References 21

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