A Comparison of PHY-Based Fingerprinting Methods Used to Enhance Network Access Control

Network complexity continues to evolve and more robust measures are required to ensure network integrity and mitigate unauthorized access. A physical-layer (PHY) augmentation to Medium Access Control (MAC) authentication is considered using PHY-based Distinct Native Attribute (DNA) features to form device fingerprints. Specifically, a comparison of waveform-based Radio Frequency DNA (RF-DNA) and Constellation-Based DNA (CB-DNA) fingerprinting methods is provided using unintentional Ethernet cable emissions for 10BASE-T signaling. For the first time a direct comparison is achievable between the two methods given the evaluation uses the same experimentally collected emissions to generate RF-DNA and CB-DNA fingerprints. RF-DNA fingerprinting exploits device dependent features derived from instantaneous preamble responses within communication bursts. For these same bursts, the CB-DNA approach uses device dependent features derived from mapped symbol clusters within an adapted two-dimensional (2D) binary constellation. The evaluation uses 16 wired Ethernet devices from 4 different manufacturers and both Cross-Model (manufacturer) Discrimination (CMD) and Like-Model (serial number) Discrimination (LMD) is addressed. Discrimination is assessed using a Multiple Discriminant Analysis, Maximum Likelihood (MDA/ML) classifier. Results show that both RF-DNA and CB-DNA approaches perform well for CMD with average correct classification of

$$\%C$$

=90% achieved at Signal-to-Noise Ratios of

$$SNR\ge 12.0$$

dB. Consistent with prior related work, LMD discrimination is more challenging with CB-DNA achieving

$$\%C$$

=90.0% at

$$SNR$$

=

$$22.0$$

dB and significantly outperforming RF-DNA which only achieved

$$\%C$$

=56.0% at this same

$$SNR$$

.