The diffusion layers in substitution-permutation network（SPN） block ciphers are almost invertible linear transformations, which is optimal if the branch number reaches the maximum value. The method of constructing i...The diffusion layers in substitution-permutation network（SPN） block ciphers are almost invertible linear transformations, which is optimal if the branch number reaches the maximum value. The method of constructing involutory optimal diffusion layers is proposed based on the Cauchy matrix, which can decrease the cost of implementation. The analysis to experimental results indicates that the diffusion layer ensures the security of the SPN block cipher against differential cryptanalysis（DC） and linear cryptanalysis（LC）, and decreases half the cost of implementation.展开更多
Sum-product networks(SPNs)are an expressive deep probabilistic architecture with solid theoretical foundations,which allows tractable and exact inference.SPNs always act as black-box inference machine in many artifici...Sum-product networks(SPNs)are an expressive deep probabilistic architecture with solid theoretical foundations,which allows tractable and exact inference.SPNs always act as black-box inference machine in many artificial intelligence tasks.Due to their recursive definition,SPNs can also be naturally employed as hierarchical feature extractors.Recently,SPNs have been successfully employed as autoencoder framework in representation learning.However,SPNs autoencoder ignores the model structural duality and trains the models separately and independently.In this work,we propose a Dual-SPNs autoencoder which designs two SPNs autoencoders to compose as a dual form.This approach trains the models simultaneously,and explicitly exploits the structural duality between them to enhance the training process.Experimental results on several multilabel classification problems demonstrate that Dual-SPNs autoencoder is very competitive against with state-of-the-art autoencoder architectures.展开更多
Substitution permutation network (SPN) is one important structure of block cipher cryptosystems. Prior work has shown different fault analyses on SPN. The formalization of fault analysis of both attack and protect on ...Substitution permutation network (SPN) is one important structure of block cipher cryptosystems. Prior work has shown different fault analyses on SPN. The formalization of fault analysis of both attack and protect on SPN have been given. The overhead and time tolerance of fault detection have been discussed. The pseudo-blinding method to detect fault attack is introduced, and the balance of the security, overhead and time tolerance based on the evaluation could be made.展开更多
文摘The diffusion layers in substitution-permutation network（SPN） block ciphers are almost invertible linear transformations, which is optimal if the branch number reaches the maximum value. The method of constructing involutory optimal diffusion layers is proposed based on the Cauchy matrix, which can decrease the cost of implementation. The analysis to experimental results indicates that the diffusion layer ensures the security of the SPN block cipher against differential cryptanalysis（DC） and linear cryptanalysis（LC）, and decreases half the cost of implementation.
基金the National Natural Science Foundation of China(No.61472161)the Science&Technology Development Project of Jilin Province(Nos.20180101334JC and 20160520099JH)。
文摘Sum-product networks(SPNs)are an expressive deep probabilistic architecture with solid theoretical foundations,which allows tractable and exact inference.SPNs always act as black-box inference machine in many artificial intelligence tasks.Due to their recursive definition,SPNs can also be naturally employed as hierarchical feature extractors.Recently,SPNs have been successfully employed as autoencoder framework in representation learning.However,SPNs autoencoder ignores the model structural duality and trains the models separately and independently.In this work,we propose a Dual-SPNs autoencoder which designs two SPNs autoencoders to compose as a dual form.This approach trains the models simultaneously,and explicitly exploits the structural duality between them to enhance the training process.Experimental results on several multilabel classification problems demonstrate that Dual-SPNs autoencoder is very competitive against with state-of-the-art autoencoder architectures.
基金National Natural Science Foundation ofChina(No.60573031)Foundation of Na-tional Laboratory for Modern Communica-tions(No.51436060205JW0305)Founda-tion of Senior Visiting Scholarship of Fu-dan University
文摘Substitution permutation network (SPN) is one important structure of block cipher cryptosystems. Prior work has shown different fault analyses on SPN. The formalization of fault analysis of both attack and protect on SPN have been given. The overhead and time tolerance of fault detection have been discussed. The pseudo-blinding method to detect fault attack is introduced, and the balance of the security, overhead and time tolerance based on the evaluation could be made.
