基于改进BP神经网络的ATM系统信息安全评估方法

摘要

根据ATM系统3层体系结构,针对ATM系统面临的信息安全问题,提出了应用人工神经网络(ANN)技术来评估ATM系统信息安全的思想;设计了基于改进的BP ANN的ATM系统3层神经网络评估模型.根据建立的BP神经网络模型,以ATM信息系统主要信息安全指标作为训练样本,通过学习和训练找出输入与输出之间的内在联系,用训练好的BP网络对ATM信息系统进行评估,并将评估结果与传统的评估方法进行比较.实验结果表明,提出的评估模型具有很强的自适应性和容错能力,适用于复杂的ATM信息系统的安全性评估.实验数据与实际ATM信息系统的运行状态相吻合.%ATM system was divided into 3 layers for the purpose of evaluating its information security.An evaluation model was proposed by using a 3-layer artificial neural network (ANN) based on improved BP model.The major information security indicators of ATM system were used as the training samples, which were adapted to find the intrinsic links between the input and output by learning and training process.An experiment was conducted by using the well-trained ANN network to evaluate the security of ATM system.The experimental results show that the proposed ANN evaluation model can indicate the practical running status of ATM system precisely.It is highly adaptive and fault-tolerant.