• DocumentCode
    3529068
  • Title

    Gabor-based RF-DNA fingerprinting for classifying 802.16e WiMAX Mobile Subscribers

  • Author

    Reising, Donald R. ; Temple, Michael A. ; Oxley, Mark E.

  • Author_Institution
    US Air Force Inst. of Technol., Wright-Patterson AFB, OH, USA
  • fYear
    2012
  • fDate
    Jan. 30 2012-Feb. 2 2012
  • Firstpage
    7
  • Lastpage
    13
  • Abstract
    Previous work has demonstrated the viability of using RF-DNA fingerprinting to provide serial number discrimination of IEEE 802.11a WiFi devices as a means to augment conventional bit-level security. This was done using RF-DNA extracted from signal regions containing standard pre-defined responses (preamble, midamble, etc.). Using these responses, proof-of-concept demonstrations with RF-DNA fingerprinting have shown some effectiveness for providing serial number discrimination. The discrimination challenge increases considerably when pre-defined signal responses are not present. This challenge is addressed here using experimentally collected IEEE 802.16e WiMAX signals from Alvarion BreezeMAX Mobile Subscriber (MS) devices. Relative to previous Time Domain (TD) and Spectral Domain (SD) fingerprint features, joint time-frequency Gabor (GT) and Gabor-Wigner (GWT) Transform features are considered here as a means to extract greater device discriminating information. For comparison, RF-DNA is extracted from TD, SD, GT, and GWT responses and MDA/ML feature extraction and classification performed. Preliminary assessment shows that Gabor-based RF-DNA fingerprinting is much more effective than either TD or SD methods. GT RF-DNA fingerprinting achieves individual WiMAX MS device classification of 98.5% or better for SNR ≥ -3 dB.
  • Keywords
    DNA; WiMax; fingerprint identification; image classification; mobile radio; spectral-domain analysis; subscriber loops; time-domain analysis; time-frequency analysis; wireless LAN; Alvarion BreezeMAX mobile subscriber devices; Gabor-Wigner transform features; Gabor-based RF-DNA fingeprinting; IEEE 802.11a WiFi devices; IEEE 802.16e WiMAX mobile subscribers classification; MDA-ML feature extraction; SD methods; TD methods; bit-level security; proof-of-concept demonstrations; signal regions; spectral domain fingerprint features; standard pre-defined signal responses; time domain fingerprint features; time-frequency Gabor transform features; Feature extraction; IEEE 802.16 Standards; Noise measurement; Signal to noise ratio; Time frequency analysis; Transforms; WiMAX;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing, Networking and Communications (ICNC), 2012 International Conference on
  • Conference_Location
    Maui, HI
  • Print_ISBN
    978-1-4673-0008-7
  • Electronic_ISBN
    978-1-4673-0723-9
  • Type

    conf

  • DOI
    10.1109/ICCNC.2012.6167534
  • Filename
    6167534