5 papers
Deep Attention Recognition for Attack Identification in 5G UAV scenarios: Novel Architecture and End-to-End Evaluation
Joseanne Viana, Hamed Farkhari, Pedro Sebastiao +5
Despite the robust security features inherent in the 5G framework, attackers will still discover ways to disrupt 5G unmanned aerial vehicle (UAV) operations and decrease UAV contro…
A Synthetic Dataset for 5G UAV Attacks Based on Observable Network Parameters
Joseanne Viana, Hamed Farkhari, Pedro Sebastiao +4
Synthetic datasets are beneficial for machine learning researchers due to the possibility of experimenting with new strategies and algorithms in the training and testing phases. Th…
A Convolutional Attention Based Deep Network Solution for UAV Network Attack Recognition over Fading Channels and Interference
Joseanne Viana, Hamed Farkhari, Luis Miguel Campos +5
When users exchange data with Unmanned Aerial vehicles - (UAVs) over air-to-ground (A2G) wireless communication networks, they expose the link to attacks that could increase packet…
Calibration of the 5G-LENA System Level Simulator in 3GPP reference scenarios
Katerina Koutlia, Biljana Bojovic, Zoraze Ali +1
Due to the rapid technology evolution and standardization activity in the mobile communication networks, there is the need for the research community to be able to develop, test an…
Design and Experimental Validation of a Software-Defined Radio Access Network Testbed with Slicing Support
K. Koutlia, R. Ferrus, E. Coronado +4
Network slicing is a fundamental feature of 5G systems to partition a single network into a number of segregated logical networks, each optimized for a particular type of service,…