According to that fake finger vein images can successfully attack finger vein recognition system， making the safety performance significantly reduced， this paper proposes a novel method for finger vein spoofing attack detection based on Deep Belief Network. Through the unsupervised training layerbylayer to get the weight parameters of the depth network and the supervised BP neural network to finetune the weight parameters， we extract the feature of the finger vein image and detect the vein image. Obtained experiment results show that the proposed scheme can effectively identify the fake finger vein image. Through comparative experimental research， we find that the proposed scheme can improve the safety performance of the recognition system.