Abstract: The power information system uses smart power grids to manage power equipment. With the increase of the total amount of social electricity consumption and the promotion and development of smart power grids, the scale of power network gradually becomes larger and the management is complex. However, it is important to ensure the security of power information system. Network intrusion detection technology can effectively avoid the intrusion and attack from the network, and then ensure the security of the system. In this paper, Dueling-DDQN algorithm of deep reinforcement learning method is used to solve the problem of intrusion detection in the network. The agent obtains reward value according to the trial and error learning to train the algorithm, so as to improve the efficiency of network intrusion detection and reduce the labor cost at the same time. Finally, the NLS-KDD data set is used for comparative experiments, and the experimental results show that the network intrusion detection algorithm based on Dueling-DDQN can improve the detection efficiency, and then better protect the network security.

Key words: intrusion detection, network security, power information network, deep reinforcement learning