Abstract
The public key cryptography based on an Overstoraged Hopfield Neural Network (OHNN) is a combination of Diffie-Hellman public key cryptosystem and probabilistic symmetric-key encryption scheme with chaotic-classified properties. Keep the random permutation operation of the neural synaptic matrix as the secret key, and the neural synaptic matrix after permutation as public-key. Because of the principal applications of generalized inverses is to the solution of linear systems and matrix equations in the singular case, we use the generalized inverse of matrices to demonstration that the transform function of the neural synaptic matrix is trapdoor one-way function. It lays a good foundation to design a provably secure public-key encryption scheme.
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