基于PCA和改进BP神经网络的信息安全评估模型构建

Construction of information security evaluation model based on PCA and improved BP neural network

为了提高空间维度循环感知网络传输信息的安全性,构建基于PCA和改进BP神经网络的信息安全评估模型.首先通过空间维度循环感知网络信息的数据存储结构特征分析和集成处理,对空间维度循环感知网络信息的主成分特征分布加密和编码,再采用主成分特征分布循环密钥构造分析和算术编码方法,得到面对不同数据库结构模型的网络信息分布知识库,然后构建网络信息的主成分特征分布密码结构,获取密钥安全评估协议的网络信息自相关函数,最后采用改进BP神经网络,实现信息安全评估模型的构建.测试表明,采用该方法进行空间维度循环感知网络传输信息安全评估的加密性能较好,提高信息输出的安全性和抗攻击能力.

In order to improve the security of information transmitted by spatial dimension loop-aware networks,an information security evaluation model based on PCA and improved BP neural network is constructed.Firstly,the data storage structure features are analyzed and the information data is integrated in spatial dimension loop-aware networks.Secondly,the principal component feature distribution of the informative data is encrypted and encoded in spatial dimension loop-aware networks.Thirdly,the spatial dimension loop-aware networks information distribution knowledge base of different database structure models is obtained by adopting the principal component feature distribution circular key construction analysis and arithmetic coding method.Next,the coded feature distribution of the key security assessment protocol is obtained by constructing the principal component feature distribution cryptographic structure of the spatial dimension loop-aware network information.Finally,the improved BP neural network is used to realize the construction of information security evaluation model.The test results show that using this method to transmit information the in spatial dimension loop-aware networks the encryption performance of the security evaluation is better,and the security and anti-attack ability of information output can be effectively improved.