In this paper we explore the feasibility of device fingerprinting under challenging realistic settings, by identifying artifacts in the transmitted signals ...
In this paper we explore the feasibility of device fingerprinting under challenging realistic settings, by identifying artifacts in the transmitted signals ...
In this paper we explore the feasibility of device fingerprinting under challenging realistic settings, by identifying artifacts in the transmitted signals ...
RF-DCN is developed, a novel Deep Complex-valued Neural Network that operates on raw RF signals and is completely agnostic of the underlying applications ...
... A recurrent deep complex-valued network (RDCN) is proposed to fingerprint devices using raw I/Q data from Wi-Fi and ADS-B signals [33] . For its performance ...
Nov 10, 2020 · Bibliographic details on Chameleons' Oblivion: Complex-Valued Deep Neural Networks for Protocol-Agnostic RF Device Fingerprinting.
Sep 18, 2019 · Abstract:Researchers have demonstrated various techniques for fingerprinting and identifying devices. Previous approaches have identified ...
Missing: Chameleons' Oblivion:
Chameleons' oblivion: Complex-valued deep neural networks for protocol-agnostic RF device fingerprinting. I Agadakos, N Agadakos, J Polakis, MR Amer.
Chameleons' Oblivion: Complex-Valued Deep Neural Networks for Protocol-Agnostic RF Device Fingerprinting · Ioannis Agadakos, Nikolaos Agadakos, Jason Polakis ...
Chameleons' oblivion: complex-valued deep neural networks for protocolagnostic RF device fingerprinting. In: 2020 IEEE European Symposium on Security and ...
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