Abstract

Due to personal privacy, information security is a particularly important issue in wireless body area networks. Although current communication protocol has considered the security, there is still a risk that lapses in physical layer security may be a potential threat in wireless body area networks. In order to achieve the comprehensive security protection, in this article, we propose a cross-layer authentication approach, where the higher layer and physical layer are simultaneously considered. More specifically, different from current literatures, we exploit the sparse representation of the original signal as the basis of physical layer authentication, and a representative selection algorithm is presented to achieve the signal detection. Moreover, based on IEEE Standard 802.15.6, we give a feasible unite authentication scheme, in which physical layer strategy and higher layer strategy are combined to enhance the security of authentication. To verify the effectiveness of the proposed physical layer strategy, we conducted experiments and numerical simulations. Furthermore, the computational complexity of the proposed algorithm and the efficiency of the cross-layer approach are analyzed, respectively. Results showed that the proposed approach can significantly enhance the authentication and the complexity is acceptable (polynomial complexity).

Highlights

  • A new generation of ubiquitous body-centric systems, wireless body area networks (WBANs),[1,2] is expected to reduce the healthcare stress

  • The raw data are preprocessed based on sparse representation, and we proposed a representative selection algorithm (RSA) to achieve the spoofing detection

  • We present the details of physical layer strategy, which includes signal preprocessing based on sparse representation, RSA, and binary hypothesis test

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Summary

Introduction

A new generation of ubiquitous body-centric systems, wireless body area networks (WBANs),[1,2] is expected to reduce the healthcare stress. Different from current literatures, in this study, we present a new physical layer spoofing detection scheme based on a deeper feature representation of original signal, where the distinguishability of original signal is further highlighted to enhance the authentication performance. In this article, our main contributions can be mainly summarized as follows: (1) we proposed a new physical layer spoofing detection scheme based on sparse representation to enhance the detection performance and (2) for practical application, we give a feasible cross-layer approach to message authentication for WBANs. The rest of this article is organized as follows.

Results
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