Abstract: Railway internet ticketing system had replaced the conventional ticket transaction method which was playing an important part in railway transportation production. As a result of the Internet-based character, railway internet ticketing system was facing several levels of security risks and threats such as overt aggressions and virus infections. Once the system was break down, a great negative impact would be brought to the society. Based on the threats referred, scientific methods and tools need to be used to analyze the threats vulnerability of the system; consequences caused by the security incidents should also be evaluated once the accidents occurred. Protection countermeasures and corrective measures against threats should be proposed to control and mitigate information security risks which should bring the threats to an acceptable level. Artificial neural networks (ANN) has intelligent character such as autonomously access knowledge which can better deal with uncertainty and nonlinear problems, and it had been wildly applied in information security risk assessment in many industries. Compared with other ANN, the BP neural network had a good nonlinear mapping ability including self-learning and adaptive capacities. First, using the 3-layer neural network can approximate any nonlinear arbitrary precision continuous functions, making it suitable for solving complex problems. Second, the output can be automatically extracted "Reasonable Rules" between output data during the training process, and the learning content can adaptively memory the rules on the weights in the network. As a result, an evaluation mode was proposed by using artificial neural network based on BP model in view of safety menace of railway internet ticketing system, the major safety menaces of internet ticketing system were used as the training samples; an experiment was conducted by using the trained BP artificial neural network to evaluate the security of the internet ticketing system. The experiment results show that the proposed evaluation model can indicate the practical status of internet ticketing system precisely. It is highly adaptive and fault-tolerant.