Radio frequency (RF) fingerprinting technology has been developed as a unique method for maintaining security based on physical layer characteristics. In this paper, we propose the RF fingerprinting by extracting the parameter characteristics such as information dimension, constellation feature, and phase ...
RF fingerprinting is a key security mechanism that allows device identification by learning unchanging, hardware-based characteristics of the transmitter. In this article, we demonstrate how machine learning techniques impact RF fingerprinting by analyzing a dataset of 400 GB of in-phase (I) and quadr...
A radiofrequency (RF) fingerprinting strategy for the proper identification of wireless devices in mobile and wireless networks is proposed. The main objective is the extraction of the main parameters of the RF signal of the device by means of the preamble in the communication in the wireless net...
RF Signature Processing (RFSP) from Comtech Location Technologies Pioneering machine-based intelligence for RF fingerprinting to provide improved yield without costly maintenance. Our RFSP solution offers complementary performance in situations where other location technologies fail for many reasons, for instanc...
Radio frequency (RF) fingerprinting extracts fingerprint features from RF signals to protect against masquerade attacks by enabling reliable authentication of communication devices at the “serial number” level. Facilitating the reliable authentication of communication devices are machine learning (ML) algorit...
Machine learning algorithms, such as Random forest [32], [33] and AdaBoost [34], [35], are often used in promoting the performance of classification as well. Another important aspect influencing the localization accuracy of the fingerprinting-based localization system is the quality of finger...
Today, the most viable solution for localization is the RSS fingerprinting based approach, where in order to establish a relationship between RSS values and location, different machine learning approaches are used. The advantage of this approach based on WLAN technology is that it does not need ...
Deep Learning for RF-Based Drone Detection and Identification: A Multi-Channel 1-D Convolutional Neural Networks Approach 2020, 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020 A Survey on Device Behavior Fingerprinting: Data Sources, Techniques, Application ...
Nerguizian, C., Despins, C., and Affès, S., Lecture Notes in Computer Science (book chapter on “Indoor geolocation with received signal strength fingerprinting technique and neural networks”), Berlin: Springer, July 2004. Google Scholar Sahi, P., The Springer International Series in Engi...
Machine learning and deep learning have been applied to recognize a mobile device by extracting and analyzing its RF fingerprinting characteristics due to their powerful feature learning and representational abilities. However, the performance and accuracy of the learning algorithm will degrade dramatically ...