隐私保护的心电图身份识别技术研究

doi:10.3969/j.issn.1671-1122.2016.08.001

信息网络安全 ›› 2016, Vol. 16 ›› Issue (8): 1-5.doi: 10.3969/j.issn.1671-1122.2016.08.001

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隐私保护的心电图身份识别技术研究

管绍朋, 葛鑫, 张渊, 仲盛()

南京大学计算机系,江苏南京 210023

收稿日期:2016-06-15 出版日期:2016-08-20 发布日期:2020-05-13
作者简介:
作者简介：管绍朋（1976—）,男,山东,副教授,博士,主要研究方向为信息安全与隐私保护;葛鑫（1989—）,男,江苏,硕士研究生,主要研究方向为信息安全与隐私保护;张渊（1985—）,男,湖北,助理研究员,博士,主要研究方向为信息安全与隐私保护;仲盛（1974—）,男,江苏,教授,博士,主要研究方向为信息安全与隐私保护。
基金资助:
国家自然科学基金[61321491,61300235,61402223];国家杰出青年科学基金[61425024];江苏省双创计划

Research on Privacy Preserving ECG-based Identification Technology

Shaopeng GUAN, Xin GE, Yuan ZHANG, Sheng ZHONG()

Department of Computer Science and Technology, Nanjing University, Nanjing Jiangsu 210023, China

Received:2016-06-15 Online:2016-08-20 Published:2020-05-13

摘要/Abstract

摘要：

心电图是与个体紧密相关的生理特征,用于身份认证有着无可比拟的优势。然而,心电图反映了人体的健康状况,属于重要的个人隐私。文章提出了一种隐私保护的心电图身份识别技术,首先在数据的训练阶段和匹配阶段采用一定机制进行心电图隐私保护,然后分别采用欧几里得距离算法和互相关算法对隐私保护后的心电图数据进行识别实验。结果显示：对于公用数据库MIT-BIH Normal Sinus Rhythm Database中的心电图数据,使用欧几里得距离算法和互相关算法的识别率都能达到100%。对于公用数据库MIT-BIH Arrhythmia Database中的心电图数据,使用欧几里得距离算法和互相关算法的识别率都能达到96.77%。

关键词: 隐私保护, 心电图, 身份识别, 欧几里得距离, 互相关

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

中图分类号:

TP309

管绍朋, 葛鑫, 张渊, 仲盛. 隐私保护的心电图身份识别技术研究[J]. 信息网络安全, 2016, 16(8): 1-5.

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

图/表 5

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隐私保护的心电图身份识别技术研究

Research on Privacy Preserving ECG-based Identification Technology

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