In cognitive radio systems, there are cases where malicious users transmit interference power to prevent secondary users from transmitting information. Due to the destructive behavior of malicious users, spectrum utilization efficiency will be reduced. The applications of game theory to study this confrontation relationship are reasonable. Based on the Continuous Blotto Game (CBG) model under the condition of one-shot perfect information confrontation, this paper constructs an anti-jamming game model for power allocation confrontation between secondary users and malicious users, and simulates the competition between two players under fixed resource constraints. An evolutionary learning approach is proposed, which improves the performance of the power allocation strategy through the repeated game of two players, and can obtain the same effect as the Nash equilibrium strategy under certain conditions. Our approach realizes the optimal power allocation on the information transmission channel in interference countermeasures without knowing the power allocation strategy of malicious users, thereby realizing the optimal utilization of spectrum resources. The simulation results show that, compared with the greedy algorithm and random algorithm, our algorithm has a more obvious effect on improving the spectrum utilization of secondary users.