Comparison of Radio Frequency Distinct Native Attribute and Matched Filtering Techniques for Device Discrimination and Operation Identification
Technical Report,01 Dec 2014,24 Mar 2016
AIR FORCE INSTITUTE OF TECHNOLOGY WRIGHT-PATTERSON AFB OH WRIGHT-PATTERSON AFB United States
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The research presented here provides a comparison of the classification, verification, and computational time performance of three techniques to analyze unintentional radio-frequency RF emissions URE from semiconductor devices for the purposes of device discrimination and operation identification. URE from ten MSP430F5529 16-bit microcontrollers were analyzed using 1 RF distinct native attributes RF-DNA fingerprints paired with multiple discriminant analysismaximum likelihood MDAML classification, 2 RF-DNA fingerprints paired with generalized relevance learning vector quantized-improved GRLVQI classification, and 3 time domain TD signals paired with matchedfiltering. These techniques were considered for potential applications to detect counterfeitTrojan hardware infiltrating supply chains and to defend against cyber attacks by monitoring the executed operations of embedded systems in critical supervisory control and data acquisition SCADA networks.
- Radiofrequency Wave Propagation
- Electrical and Electronic Equipment
- Statistics and Probability