Visual cryptography for general access structures
Information and Computation
Elements of the Theory of Computation
Elements of the Theory of Computation
Visual Authentication and Identification
CRYPTO '97 Proceedings of the 17th Annual International Cryptology Conference on Advances in Cryptology
A Neural Network Approach for Visual Cryptography
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5 - Volume 5
A neural-network approach for visual cryptography and authorization
Design and application of hybrid intelligent systems
The semipublic encryption for visual cryptography using Q'tron neural networks
Journal of Network and Computer Applications - Special issue: Network and information security: A computational intelligence approach
The semipublic encryption for visual cryptography using q'tron neural networks
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
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This paper proposes the general paradigm to build Q'tron neural networks (NNs) for visual cryptography. Given a visual encryption scheme, usually described using an access structure, it was formulated as a optimization problem of integer programming by which the a Q'tron NN with the so-called integer-programming-type energy function is, then, built to fulfill that scheme. Remarkably, this type of energy function has the so-called known-energy property, which allows us to inject bounded noises persistently into Q'trons in the NN to escape local minima. The so-built Q'tron NN, as a result, will settle down onto a solution state if and only if the instance of the given encryption scheme is realizable.