Aiming at the problems of low efficiency of relay selection algorithm and security threat of potential eavesdropping nodes in multi-relay communication network. A joint relay and jammer selection strategy based on artificial neural network is proposed. Firstly, the decode-and-forward ( DF ) relay protocol is adopted to construct the multi-relay cooperative communication network with eavesdropper, and the closed form expression of the security outage probability is derived by combination with the cooperative jamming strategy. Then, the neural network is trained, and the channel state information (CSI) of the relevant nodes is taken as the input data to train the model to obtain the optimal model parameters. Finally, some data sets are used to verify the model, and the simulation results show that the accuracy of optimal nodes selection can reach more than 93%. Compared with the traditional selection scheme based on exhaustive search and support vector machine, the proposed scheme reduces the implementation complexity and computation time significantly, and effectively improve the security performance of the system.