The semipublic encryption for visual cryptography using Q'tron neural networks

The paper proposes the semipublic encrypting scheme for visual cryptography using the Q'tron neural-network (Q'tron NN) model. This encrypting scheme hides only the true secret from the public. That is, the pictorial meaning appearing in a public share describes the public information in a document while leaving its confidential part undisclosed. A piece of confidential information is retrievable if and only if a right user share is available. The method to construct the Q'tron NN to fulfill the aforementioned scheme will be investigated. An application that uses the scheme for key distribution in a public area will be demonstrated.