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Proceedings Paper

RF device forensics using passband filter analysis
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Paper Abstract

Given the wide use of Radio Frequency (RF) devices for applications ranging from data networks to wireless sensors, it is of interest to be able to characterize individual devices to verify compliance with FCC Part 15 rules. In an effort to characterize these types of devices we have developed a system that utilizes specially designed probe signals to elicit a response from the device from which unique characteristics can be extracted. The features that uniquely characterize a device are referred to as device signatures or device fingerprints. We apply this approach to RF devices which employ different bandpass filters, and construct training based classifiers which are highly accurate. We also introduce a model-based framework for optimal detection that can be employed to obtain performance limits, and to study model mismatch and probe optimization.

Paper Details

Date Published: 4 February 2009
PDF: 12 pages
Proc. SPIE 7254, Media Forensics and Security, 725419 (4 February 2009); doi: 10.1117/12.806056
Show Author Affiliations
Deen King-Smith, Purdue Univ. (United States)
Aravind K. Mikkilineni, Purdue Univ. (United States)
Saul Gelfand, Purdue Univ. (United States)
Edward J. Delp, Purdue Univ. (United States)

Published in SPIE Proceedings Vol. 7254:
Media Forensics and Security
Edward J. Delp; Jana Dittmann; Nasir D. Memon; Ping Wah Wong, Editor(s)

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