摘要
手写签名认证技术作为一种有效的生物特征识别技术,具有易于采集、难以模仿、不易伪造的优点。文章提出一种采用马尔可夫状态转移概率矩阵为特征,BP神经网络为用户身份识别分类器的手机身份认证方法。基于Android手机平台和Java语言,实现了文章提出的手机身份认证系统,实验结果证明所提出的基于Markov-BP神经网络的手写签名身份认证系统的有效性。
As an effective biometric identification technology ,handwritten signature authentication technology is easy to collect, inimitable and anti-counterfeit. This paper proposes a mobile phone identity authentication method with the Markov state transition probability matrix as characteristics, and BP neural network as Identity recognition classifier of users. Based on Android cellphone platform and Java language, the mobile phone identity authentication system is implemented. And the handwritten Signature authentication system based on Markov-BP Neural Network is proved effective by experimental results.
出处
《信息网络安全》
2013年第9期64-67,共4页
Netinfo Security
基金
教育部中国移动科研基金[MCM20122062]
