Antenna Additively Manufactured Engineered Fingerprinting for Physical-Layer Security Enhancement for Wireless Communications

Abstract

Physical layer security is increasingly being exploited as a technique to enhance the security of wireless communications. Well-known hardware security techniques leverage unintended manufacturing process variations or fixed unique hardware structures in the semiconductors for identification of different copies of an RF system. The fundamentally different concept of engineering a unique fingerprint for each antenna produced, by leveraging additive manufacturing, is presented in this work. To the best of the author's knowledge, this is the first application of the concept of radio frequency (RF) fingerprint engineering using additively manufactured (AM) antennas for hardware-based security mechanisms. AM engineered fingerprints (AMEF) are based on intentional features added to antenna's geometries using 3D printing, enabling more accurate signal source identification and classification. Such unique features per unit produced would be prohibitively costly by using traditional photolithographic processes. The AMEF concept is validated using AM right hand circularly polarized (RHCP) truncated corner probe fed (TCPF) patch antennas and a testbed setup with software-defined radios and MATLAB implementations to create, transmit, receive, and prepare a convolutional neural network (CNN) to classify the transmitted raw I/Q data of Wi-Fi signals (IEEE 802.11). The AMEF technique greatly improves the physical layer security performance limitations in large-scale applications where the features of the devices can overlap, at a low-cost and low production time impact, and it allows the use of the antenna features for both individual and type classification and identification of RF sources.