Simulcasted Power Line Communication Network (SPN) Configuration Validation for Home Automation Applications Using Wired Signal Distinct Native Attribute (WS-DNA) Fingerprinting

Abstract:

By utilising existing infrastructure, Power Line Communication (PLC) is a cost- effective, practical solution that supports home automation and critical national infrastructure systems. However, current home automation PLC implementations are inherently unsecure, susceptible to network intrusion, and vulnerable to unauthorised configuration changes. This work presents Wired Signal Distinct Native Attribute (WS-DNA) Fingerprinting as a compelling method for PLC network intrusion detection via Physical-Layer (PHY) discrimination using a Multiple Discriminant Analysis (MDA) classifier. Results are presented using single- and multiple-device fingerprints that detect network configuration changes at a rate of 90% and 75%, respectively.


AUTHORS

Photo of Brady Ross

Department of Electrical and Computer Engineering Air Force Institute of Technology Wright-Patterson Air Force Base 
Dayton, OH, U.S.A

Brady Ross was commissioned into the U.S. Air Force as a military officer in 2012.  He earned a bachelor’s degree in Mathematics from Stephen F. Austin University and a bachelor’s degree in Electrical Engineering from the University of Texas at Tyler.  He also earned a master’s degree in Electrical Engineering (with a focus on digital systems design and evaluation) from the Air Force Institute of Technology.

Photo of Dr. Timothy J. Carbino

Department of Electrical and Computer Engineering Air Force Institute of Technology Wright-Patterson Air Force Base 
Dayton, OH, U.S.A

Dr. Timothy J. Carbino is a Professor of Electrical Engineering in the Department of Electrical and Computer Engineering at the Air Force Institute of Technology. He earned a bachelor’s degree in Civil Engineering from the University of Florida (2006), a master’s degree in Mechanical Engineering from the Air Force Institute of Technology (2012), and a doctorate from the Air Force Institute of Technology (2015). His research interests include device identification using Wired Signal Distinct Native Attributes (WS-DNA) Fingerprinting via Constellation Based DNA (CB- DNA) development and Radio Frequency DNA (RF- DNA). He has been a member of the Institute of Electrical and Electronics Engineers (IEEE) since 2013.

Photo of Dr. Michael A. Temple

Department of Electrical and Computer Engineering Air Force Institute of Technology Wright-Patterson Air Force Base 
Dayton, OH, U.S.A

Dr. Michael A. Temple is a Professor of Electrical Engineering in the Department of Electrical and Computer Engineering at the Air Force Institute of Technology.  He earned bachelor’s (1985) and master’s (1986) degrees in Engineering from Southern Illinois University, and a doctorate from the Air Force Institute of Technology (1993). His research interests include passive emitter identification, and tracking and locating using RF Distinct Native Attribute (RF-DNA) Fingerprinting. Recently, he has participated in the expansion of RF- DNA fundamentals to support additional Wired Signal DNA (WS-DNA) and Constellation/Correlation Based DNA (CB-DNA) applications.  His primary research emphasis remains focused on commercial communication devices with reliable, human-like device/signal discrimination achieved for various signals (Wi-Fi, WiMAX, ZigBee, ZWave, Ethernet, and Insteon).  His sponsored research activity continues in Command, Control, Communications and Intelligence (C3I), radar signal/signature processing, and Electronic Warfare (EW).

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Keywords

C

C2
C2S
CDX
CIA
CIP
CPS

I

IA
ICS

S

SOA

X

XRY

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