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Cascade Forward Back-propagation Neural Network Based Group Authentication Using (n, n) Secret Sharing Scheme

机译:使用(n,n)秘密共享方案的基于级联正向反向传播神经网络的组认证

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Authentication is the important issue over the internet. It results in need of robust security services and schemes. This paper proposes the Shamir Secret Sharing Scheme along with Cascade forward back propagation neural network. The proposed (n, n) Shamir secret sharing scheme is implemented successfully for share encryption and decryption process. It reveals the secret only and only when all the n number of participants are available at the reconstruction process. The generated shares have a best quality so that human brain can’t predict the original secret by any combination. The neural network is already trained for RGB image database and images are stored in particular group having a group category number which is to be predicted as output of neural network. For testing purpose, we take an image, store it in a group, create its shares and now identifies to which group it belongs. The neural network here provides the correct group of that image which we have trained earlier.
机译:身份验证是Internet上的重要问题。这导致需要健壮的安全服务和方案。本文提出了“沙米尔秘密共享方案”以及级联反向传播神经网络。提出的(n,n)Shamir秘密共享方案已成功实现,用于共享加密和解密过程。仅在重建过程中所有n个参与者都可用时,它才揭示秘密。生成的共享具有最佳质量,因此人脑无法通过任何组合来预测原始秘密。已经为RGB图像数据库训练了神经网络,并且将图像存储在具有组类别编号的特定组中,该组类别编号将被预测为神经网络的输出。为了进行测试,我们拍摄一张图像,将其存储在一个组中,创建其共享,然后确定它属于哪个组。这里的神经网络提供了我们之前训练过的图像的正确组。

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