Physical-Layer discrimination of Power Line Communications

Power Line Communication (PLC) is consistently looked at as a cost effective and elegant solution for many large scale control and automation communication problems. This includes many critical infrastructure Supervisory Control and Data Acquisition (SCADA) systems. Because of this, PLC is investigated for the purposes of Wired Signal Distinct Native Attribute (WS-DNA) Physical-Layer (PHY) classification and validation as an effective intrusion detection method for PLC networks. This investigation captured intentional PLC messages, extracted WSDNA fingerprints, and utilized Multiple Discriminant Analysis, Maximum Likelihood (MDA/ML) to perform device discrimination. The modulated communication signals of six Insteon Hub devices were investigated to assess the ability to perform device discrimination and validation. For all six devices, an average correct classification of %C = 90% is achieved at Signal to Noise Ratio (SNR) ≥ 40 dB and %C = 99% at SNR ≥ 46 dB. Receiver Operating Characteristic (ROC) curves are used to illustrate rogue detection results with Equal Error Rate (EER) of 10% achieved at SNR = 40 dB.