Security of Wireless Devices using Biological-Inspired RF Fingerprinting Technique

Saeed ur Rehman, Shafiq Alam, Iman T Ardekani

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Radio Frequency (RF) fingerprinting is a security mechanism inspired by biological fingerprint identification systems. RF fingerprinting is proposed as a means of providing an additional layer of security for wireless devices. RF fingerprinting classification is performed by selecting an "unknown" signal from the pool, generating its RF fingerprint, and using a classifier to correlate the received RF fingerprint with each profile RF fingerprint stored in the database. Unlike a human biological fingerprint, RF fingerprint of a wireless device changes with the received Signal to Noise Ratio (SNR) and varies due to mobility of the transmitter/receiver and environment. The variations in the features of RF fingerprints affect the classification results of the RF fingerprinting. This chapter evaluates the performance of the KNN and neural network classification for varying SNR. Performance analysis is performed for three scenarios that correspond to the situation, when either transmitter or receiver is mobile, and SNR changes from low to high or vice versa.

Original languageEnglish
Title of host publicationBiologically-Inspired Techniques for Knowledge Discovery and Data Mining
EditorsShafiq Alam, Gillian Dobbie, Yun Sing Koh, Saeed ur Rehman
Place of PublicationHershey, Pennsylvania, USA
PublisherIGI Global
Chapter15
Pages311-330
Number of pages20
ISBN (Electronic)9781466660793
ISBN (Print)9781466660786
DOIs
Publication statusPublished - 2014

Publication series

NameAdvances in Data Mining and Database Management (ADMDM) book series
PublisherIGI Global
ISSN (Print)2327-1981
ISSN (Electronic)2327-199X

Keywords

  • Radio Frequency (RF) fingerprinting
  • wireless devices
  • Signal to Noise Ratio (SNR)

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  • Cite this

    ur Rehman, S., Alam, S., & Ardekani, I. T. (2014). Security of Wireless Devices using Biological-Inspired RF Fingerprinting Technique. In S. Alam, G. Dobbie, Y. S. Koh, & S. U. Rehman (Eds.), Biologically-Inspired Techniques for Knowledge Discovery and Data Mining (pp. 311-330). (Advances in Data Mining and Database Management (ADMDM) book series). IGI Global. https://doi.org/10.4018/978-1-4666-6078-6.ch015