In 5G and beyond networks, Unmanned Aerial Vehicles (UAV) are an attractive solution to enhance the secrecy of a wireless systems by exploiting their predominant LOS links and spacial manoeuvrability to introduce a friendly jamming. In this work, we investigate the impact of two cooperative UAVbased jammers on the secrecy performance of a ground wireless wiretap channel by considering secrecy-area related metrics, the jamming coverage and jamming efficiency. Moreover, we propose a hybrid metric, the so-called Weighted Secrecy Coverage (WSC) that can be used as a metric for gaining insights on the optimal deployments of the UAV jammers to provide the best exploration of jamming signals. For evaluating these metrics, we derive a closed-form position-based metric, the secrecy improvement, and propose an analogous computationally simpler metric. Our simulations show that a balanced power allocation between the two UAVs leads to the best performances, as well as a symmetrical positioning behind the line of sight between the legitimate transmitter and receiver. Moreover, there exist an optimal UAV height for the jammers. Finally, we propose a suboptimal and simpler problem for the maximisation of the WSC.

In this work, we investigate the impact of two cooperative unmanned aerial vehicle (UAV)-based jammers on the secrecy performance of a ground wireless network in the presence of an eavesdropper. For that purpose, we investigate the secrecyarea related metrics, Jamming Coverage and Jamming Efficiency. Moreover, we propose a hybrid metric, the so-called Weighted Secrecy Coverage (WSC) and a virtual distributed multiple-inputmultiple-output (MIMO)-based zero-forcing precoding scheme to avoid the jamming effects on the legitimate receiver. For evaluating these metrics, we derive a closed-form position-based metric, the secrecy improvement. Our mathematical derivations and comparative simulations show that the proposed zero-forcing scheme leads to an improvement on the secrecy performance in terms of the WSC, and provides conditions for improvement of Jamming Efficiency. They also show positioning trends on the UAVs over a fixed orbit around the legitimate transmitter as well as power allocation trends for optimal secrecy.

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Unmanned Aerial Vehicles (UAVs) are becoming increasingly attractive for the ambitious expectations for 5G and beyond networks due to their several benefits. Indeed, UAV-assisted communications introduce a new range of challenges and opportunities regarding the security of these networks. Thus, in this paper we explore the opportunities that UAVs can provide for physical layer security solutions. Particularly, we analize the secrecy performance of a ground wireless communication network assisted by two friendly UAV jammers in the presence of an eavesdropper. To tackle the secrecy performance of this system, we introduce a new area-based metric, the weighted secrecy coverage, that measures the improvement on the secrecy performance of a system over a certain physical area given by the introduction of friendly jamming. Herein, the optimal 3D positioning of the UAVs and the power allocation is addressed in order to maximize the WSC. For that purpose, we provide a Reinforcement Learning-based solution by modeling the positioning problem as a Multi-Armed Bandit problem over three positioning variables for the UAVs: angle, height and orbit radius. Our results show that there is a trade-off between expediency of the positioning of the UAVs to positions of better secrecy outcome and energy expenditure, and that the proposed algorithm efficiently converges into a stable state.

Unmanned aerial vehicles (UAVs) are becoming increasingly attractive for the ambitious expectations for 5G and beyond networks due to their several benefits. Indeed, UAV-assisted communications introduce a new range of challenges and opportunities regarding the security of these networks. Thus, in this paper we explore the opportunities that UAVs can provide for physical layer security solutions. Particularly, we analyse the secrecy performance of a ground wireless communication network assisted by N friendly UAV jammers in the presence of an eavesdropper. To tackle the secrecy performance of this system, we introduce a new area-based metric, the weighted secrecy coverage (WSC), that measures the improvement on the secrecy performance of a system over a certain physical area given by the introduction of friendly jamming. Herein, the optimal 3D positioning of the UAVs and the power allocation is addressed in order to maximise the WSC. For that purpose, we provide a reinforcement learning-based solution by modelling the positioning problem as a multi-armed bandit problem over three positioning variables for the UAVs: angle, height and orbit radius. Our results show that the proposed algorithm improves the secrecy of the system over time in terms of the WSC, and it converges into a stable state close to the exhaustive search solution for discretised actions, where there is a trade-off between expediency of the positioning of the UAVs to positions of better secrecy outcome and energy consumption.