期刊
IEEE SYSTEMS JOURNAL
卷 5, 期 4, 页码 564-573出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSYST.2011.2165597
关键词
Biometrics; body area network; e-healthcare; electrocardiography; Gaussian mixture model; security
类别
资金
- U.S. National Science Foundation [0707944]
- Taiwan National Science Council [NSC 99-2221-E-006-016-MY3]
- Division Of Computer and Network Systems
- Direct For Computer & Info Scie & Enginr [0707944] Funding Source: National Science Foundation
The blood circulation system in a human body provides a unique and natural trust zone for secure data communications in wireless healthcare systems such as body area networks. Unfortunately, biometric signal authentication using physiological attributes in wireless healthcare has not been extensively studied. In this paper, we propose a data authentication approach utilizing electrocardiography (ECG) signal patterns for reducing key exchange overhead. The major contribution of this research is to apply stochastic pattern recognition techniques in wireless healthcare. In the proposed approach, the inter-pulse interval (IPI) signal pattern at transmitter side is summarized as a biometric authentication key using Gaussian mixture model (GMM). At the receiver side, a light-weight signature verification scheme is adopted that uses IPI signals gathered locally at the receiver. The proposed authentication scheme has the advantage of high sample misalignment tolerance. In our earlier work, we had demonstrated the concept of stochastic authentication for ECG signal, but the signature verification process and GMM authentication performance under time synchronization and various sample points were not discussed. Here, we present a new set of analytical and experimental results to demonstrate that the proposed stochastic authentication approach achieves a low half total error rate in ECG signals verification.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据