55 documents found, page 1 of 6
Deep attention recognition for attack identification in 5G UAV scenarios: Novel...
Viana, J.; Farkhari, H.; Sebastião, P.; Campos, L. M.; Koutlia, K.; Bojovic, B.; Lagén S.; Dinis, R.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 control communication performance in Air-to-Ground (A2G) links. Operating under the assumption that the 5G UAV communications infrastructure will never be entirely secure, we propose Deep Attention Recognition (DAtR) as a solution to identi...
Port request classification automation through NLP
Martins, S.; Garrido, N.; Sebastião, P.This project describes a suggested prototype to carry out the automatic classification of requests from a Port Help Desk. It intents to ascertain if the implementation of this framework is viable for this sector. For this purpose different models were employed, such as SVM, Decision Tree, Random Forest, LSTM, BERT and a SVM hierarchical model. To verify their efficiency these models were evaluated using Precisi...
Performance assessment of a RIS-empowered post-5G/6G network operating at the m...
Velez, V.; Pavia, J. P.; Souto, N.; Sebastião, P.; Correia, A.Reconfigurable Intelligent Surfaces (RISs) are considered to be a key enabling technology for 6G as they can potentially provide a boost in performance with a high energy efficiency. RISs rely on the use of arrays with a large number of low-cost quasi-passive reflecting elements which can be individually tuned in order to shape the radio wave propagation. This can effectively enable the implementation of smart ...
Accurate and reliable methods for 5G UAV jamming identification with calibrated...
Farkhari, H.; Viana, J.; Sebastião, P.; Bernardo, L.; Kahvazadeh, S.; Dinis, R.This research highlights the negative impact of ignoring uncertainty on DNN decision-making and Reliability. Proposed combined preprocessing and post-processing methods enhance DNN accuracy and Reliability in time-series binary classification for 5G UAV security dataset, employing ML algorithms and confidence values. Several metrics are used to evaluate the proposed hybrid algorithms. The study emphasizes the X...
An optimized planning tool for microwave terrestrial and satellite link design
Ferreira, E.; Sebastião, P.; Cercas, F.; Costa, C. S.; Correia, A.Today, the internet is fundamental to social inclusion. There are many people that live in remote areas, and the only way to supply internet services is through the use of microwave terrestrial and satellite systems. Thus, it is important to have efficient tools to design and optimize these systems. In this paper, a tool with the objective to shorten the time spent in the design process of microwave terrestrial...
Examination of unremitting kidney illness by utilizing machine learning classif...
Sarwar, F.; Garrido, N.; Sebastião, P.; Rehan, A.Chronic kidney disease is a rising health issue that affects millions of people worldwide. Early detection and characterization of this disease is essential for effective management and control. This disease is associated with several serious health risks, such as cardiovascular disease, increased risk of stroke, and end-stage renal disease, which can be effectively prevented by early detection and treatment. M...
YOLOX-Ray: An efficient attention-based single-staged object detector tailored ...
Raimundo, A.; Pavia, J. P.; Sebastião, P.; Postolache, O.Industrial inspection is crucial for maintaining quality and safety in industrial processes. Deep learning models have recently demonstrated promising results in such tasks. This paper proposes YOLOX-Ray, an efficient new deep learning architecture tailored for industrial inspection. YOLOX-Ray is based on the You Only Look Once (YOLO) object detection algorithms and integrates the SimAM attention mechanism for ...
A software defined radio based anti-UAV mobile system with jamming and spoofing...
Branco Ferreira, R.; Gaspar, J.; Sebastião, P.; Souto, N.The number of incidents between unmanned aerial vehicles (UAVs) and aircrafts at airports and airfields has been increasing over the last years. To address the problem, in this paper we describe a portable system capable of protecting areas against unauthorized UAVs, which is based on the use of low-cost SDR (software defined radio) platforms. The proposed anti-UAV system supports target localization and integr...
Increasing reliability on UAV fading scenarios
Viana, J.; Madeira, J.; Nidhi; Sebastião, P.; Cercas, F.; Mihovska, A.; Dinis, R.Unmanned aerial vehicles (UAVs) are the next technology to be incorporated into a telecommunications network to improve command and control on a large scale in both line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. However, there is still room for improvement in terms of reliability. This paper investigates Constant Packet Combining (CPC) and Adaptive Packet Combining (APC) techniques applied to Unma...
A convolutional attention based deep learning solution for 5G UAV network attac...
Viana, J.; Farkhari, H.; Campos, L. M.; Sebastião, P.; Koutlia, K.; Lagén, S.; Bernardo, L.; Dinis, R.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 loss and might disrupt connectivity. For example, in emergency deliveries, losing control information (i.e., data related to the UAV control communication) might result in accidents that cause UAV destruction and damage to building...