Using differential evolution to optimize 'learning from signals' and enhance network security
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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Wireless communication security is addressed using device-specific RF-DNA fingerprints in a localized regional air monitor. The targeted application includes IEEE 802.16 WiMax-based airport communications such as being proposed by the Euro control and FAA organizations–concept validation is currently underway using the Aeronautical Mobile Airport Communications System (AeroMACS) network. Security enhancement via RF-DNA fingerprinting is motivated by earlier RF-DNA work using GMSK-based intra-cellular GSM signals and OFDM-based 802.11a peer-to-peer WiFi signals. The commonality that WiMax shares with these two existing communication systems, i.e., the cellular control structure of GSM and the multi-carrier OFDM modulation of 802.11a, suggests that RF-DNA fingerprinting may be effective for WiMax device discrimination. This is important given that WiMax shares some common features that may prove detrimental, to include bit-level authentication, privacy, and security mechanisms. It is reasonable to assume that these bit-level mechanisms will come under attack as ``hackers'' apply lessons learned from their previous successes. The contributions of this paper include: 1) the introduction of a Spectral Domain (SD) RF-DNA fingerprinting technique to augment previous Time Domain (TD) and Wavelet Domain (WD) techniques, and 2) a first look at AeroMACS physical waveform features and the potential applicability of RF-DNA fingerprinting using operationally collected signals.