This chapter proposes a new method that uses a cooperative unmanned aerial vehicle (UAV) as a friendly jammer to enhance the security performance of cognitive radio networks. Herein, a secondary transmitter (ST) sends confidential messages to a secondary receiver (SR) in the presence of an external eavesdropper (Eve), and the UAV acts as a friendly jammer that degrades the decoding capability of Eve. Therefore, resource allocation in such a network must jointly optimize the transmission power and the UAV's trajectory to maximize the secrecy rate, while satisfying a given interference threshold at the primary receiver (PR). The original problem is not convex, and thus, global optimality is difficult to achieve. To address this problem, we first transform it into a more tractable form and then propose a successive convex approximation‐based algorithm for its solutions. The proposed algorithm has low computational complexity and is guaranteed to obtain at least a locally optimal solution to the original problem. Numerical results illustrate that the proposed method significantly improves the security performance of the cognitive radio networks compared to the previous methods.