Next Article in Journal
Key Bit-Dependent Side-Channel Attacks on Protected Binary Scalar Multiplication
Next Article in Special Issue
Changes in Phonation and Their Relations with Progress of Parkinson’s Disease
Previous Article in Journal
A Space-Variant Deblur Method for Focal-Plane Microwave Imaging
Previous Article in Special Issue
Activation Process of ONU in EPON/GPON/XG-PON/NG-PON2 Networks
Open AccessArticle

Physical Layer Authentication and Identification of Wireless Devices Using the Synchrosqueezing Transform

European Commission, Joint Research Centre, 21027 Ispra, Italy
*
Author to whom correspondence should be addressed.
Appl. Sci. 2018, 8(11), 2167; https://doi.org/10.3390/app8112167
Received: 9 October 2018 / Revised: 30 October 2018 / Accepted: 2 November 2018 / Published: 6 November 2018
This paper addresses the problem of authentication and identification of wireless devices using their physical properties derived from their Radio Frequency (RF) emissions. This technique is based on the concept that small differences in the physical implementation of wireless devices are significant enough and they are carried over to the RF emissions to distinguish wireless devices with high accuracy. The technique can be used both to authenticate the claimed identity of a wireless device or to identify one wireless device among others. In the literature, this technique has been implemented by feature extraction in the 1D time domain, 1D frequency domain or also in the 2D time frequency domain. This paper describes the novel application of the synchrosqueezing transform to the problem of physical layer authentication. The idea is to exploit the capability of the synchrosqueezing transform to enhance the identification and authentication accuracy of RF devices from their actual wireless emissions. An experimental dataset of 12 cellular communication devices is used to validate the approach and to perform a comparison of the different techniques. The results described in this paper show that the accuracy obtained using 2D Synchrosqueezing Transform (SST) is superior to conventional techniques from the literature based in the 1D time domain, 1D frequency domain or 2D time frequency domain. View Full-Text
Keywords: authentication; identification; security; wireless communication; machine learning authentication; identification; security; wireless communication; machine learning
Show Figures

Figure 1

MDPI and ACS Style

Baldini, G.; Giuliani, R.; Steri, G. Physical Layer Authentication and Identification of Wireless Devices Using the Synchrosqueezing Transform. Appl. Sci. 2018, 8, 2167. https://doi.org/10.3390/app8112167

AMA Style

Baldini G, Giuliani R, Steri G. Physical Layer Authentication and Identification of Wireless Devices Using the Synchrosqueezing Transform. Applied Sciences. 2018; 8(11):2167. https://doi.org/10.3390/app8112167

Chicago/Turabian Style

Baldini, Gianmarco; Giuliani, Raimondo; Steri, Gary. 2018. "Physical Layer Authentication and Identification of Wireless Devices Using the Synchrosqueezing Transform" Appl. Sci. 8, no. 11: 2167. https://doi.org/10.3390/app8112167

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop