网络安全用户身份优化认证仿真研究

Network Security User Authentication Optimization Simulation

为了增加网络安全性能,对用户分身进行认证具有重要意义。由于网络安全用户多样,且身份信息不同,需要建立多个认证体系,对身份进行认证。传统的身份认证方法,主要通过对用户身份信息进行分类归纳,进行统一的认证,当同一时间用户过多时,会出现网络安全用户身份认证时间过长及效率差的问题。提出指纹网络安全用户身份认证优化方法。上述方法先确定合法用户指纹特征的有效区域,利用Haar小波提取用户指纹特征,并嵌入到宿主图像中,建立较精确的临界可见误差模型,使得水印嵌入强度与宿主图像特征相适应,采用极坐标来进行细节匹配,弥补了传统身份认证方法安全系数低的弊端,从而完成了对网络安全的用户身份认证方法的改进。实验结果证明,所提方法和传统方法相比,大幅度提升了用户识别能力,且安全性能较高。

In order to increase the performance of network security,user authentication is important. Therefore,we proposed an optimization method of fingerprint network security user identity authentication. In the method,we first determined the effective area of the fingerprint characteristic of the legal user,and used Haar wavelet to extract the feature of user＇s fingerprint,and embedded it into the host image. We established a more accurate critical error model. The watermark embedding intensity was adapted to the characteristics of the host image. We used the polar coordinates to match the details. It made up for the disadvantages of traditional authentication method with low security coefficient,and the improvement of user identity authentication method for network security was completed. The experimental results show that compared with the traditional methods,the proposed method significantly improves the user recognition ability,and the safety performance is high.