Spectral Domain RF Fingerprinting for 802.11 Wireless Devices
Abstract
The increase in availability and reduction in cost of commercial communication devices (IEEE compliant such as 802.11, 802.16, etc) has increased wireless user exposure and the need for techniques to properly identify/classify signals for increased security measures. A communication device's emission includes intentional modulation that enables correct device operation. Hardware and environmental factors alter the ideal response and induce unintentional modulation effects. If these effects (features) are sufficiently unique it becomes possible to identify a device using its fingerprint, with potential discrimination of not only manufacturers but possibly serial numbers for a given manufacturer. Previous AFIT research has demonstrated effectiveness at RF Fingerprinting using 802.11A signals with 1) spectral correlation on Power Spectral Density (PSD) Fingerprints, 2) Multiple Discriminant Analysis/Maximum Likelihood (MDA/ML) classification with fingerprints obtained from Time Domain (TD) and Wavelet Domain (WD) statistical features. As used here, Spectral Domain (SD) fingerprinting uses the Fourier Transform to calculate PSD features for device discrimination. Results here show some improvement over the WD approach (gain approximately equal 3 dB) and significant improvement over the TD approach (gain approximately equal 8 dB gain).
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 2010
- Accession Number
- ADA517270
Entities
People
- Sheldon A. Munns
Organizations
- Air Force Institute of Technology