Comparative Analysis of RF Emission Based Fingerprinting Techniques for ZigBee Device Classification

Abstract

LR-WPAN are increasingly being fielded to complete tasks in autonomous sensor networks, industrial control systems, and other critical infrastructure. ZigBee is a versatile LR-WPAN platform that also open to risks of sophisticated bit-level attacks. PHY based security measures have been shown in previous research efforts as effective supplemental security measures that a not susceptible to bit-level attacks. This research effort intends to quantify the differences invarious RF fingerprinting techniques via comparative analysis of MDA/ML classification results. The findings herein demonstrate a methodology for the generation of CB-DNA, RF-DNA, and COR-DNA fingerprints. The results show that CB-DNA generated fingerprints had the highest mean correct classification rates followed by COR-DNA and then RF-DNA in most test cases and especially in low Eb/N0 ranges, where ZigBee is designed to operate.

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Document Details

Document Type
Technical Report
Publication Date
Mar 23, 2017
Accession Number
AD1054630

Entities

People

  • Cameron W Coon

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Computer Network Security
  • Control Systems
  • Department Of Defense
  • Detectors
  • Discriminant Analysis
  • Governments
  • Graphical User Interface
  • Literature Surveys
  • Modulation
  • Personal Area Networks
  • Radio Frequency
  • Sensor Networks
  • Software Defined Radio
  • United States Government
  • Wireless Personal Area Networks
  • Wireless Sensor Networks

Fields of Study

  • Computer science

Readers

  • Cybersecurity.
  • Life Cycle Cost Analysis
  • Radio communications and signal processing.