Security has not been at the foundation of wireless communications technology development but is becoming increasingly important. By taking into consideration the advantages of UAV technology, including but not limited to their low deployment cost, high maneuverability, strong line of sight (LOS) radio communications links with ground nodes, and ability to operate in dangerous or hostile environments have motivated my research of integrating UAV into terrestrial communication networks for enhancing next-generation wireless network security. I have developed a framework and various algorithms based on the network optimization and learning theory that leverage the 3D movement, power control, and beamforming techniques adopted by the UAVs to enhance the fundamental secrecy performance limits of terrestrial wireless communication under active and passive eavesdropping attacks. The secrecy performance is evaluated through the secrecy rate metric, which is modeled with trajectory, power, scalability, and others. constraints related to the deployment environment, attack type and quantity, and UAVnode capabilities as a non-convex optimization problem with a non-smooth objective function. To address this problem, firstly, an iterative algorithm derived from the block coordinate descent strategy is proposed to optimize the transmission power and UAV trajectory for enhancing the secrecy rate of multiple ground users under multiple eavesdropping attacks to address the search gap of scalability. Motivated by the promising results accomplished, I went one step further to ask the following questions: (1) Can machine learning algorithms be applied to further reduce the complexity and convergence time of the proposed UAV-assisted securer terrestrial wireless networks? (2) Is it possible to enhance the secrecy rate of the network without having channel state information (CSI) of the eavesdroppers to address the research gap in analyzing the practicality of mitigation techniques against eavesdropping attacks? My recent research has demonstrated practical solutions to these research questions. For future research plans regarding this research, I am interested in investigating more scenarios for optimizing the design of the UAV trajectory under a wide range of realistic constraints, such as collision avoidance, and no-fly zone restrictions. Moreover, I am motivated to research the capabilities of the UAV in the 3D space to enable novel end-to-end solutions for enabling wider use of dynamic spectrum-sharing policies. In addition, Theoretical and practical problems at the physical (PHY), medium access control (MAC), and higher layers will be investigated to enhance the fundamentals of communication support for aerial nodes in air corridors while taking into consideration limited UAV energy resources.