Autors: Durcheva, M. I., Ivanova, M. S.
Title: Verification in Information Systems: A Machine Learning Approach with Zero-Knowledge Proof and Matrix Power Functions
Keywords:

Abstract: The contemporary information systems are characterized with extensive data and document transfer, allowing their fast and real-time processing and reliable contracting. It requires the established communication channel between different parties to be secure and trustful. As a solution, in this paper we propose a zero-knowledge proof (ZKP) protocol using matrix power function (MPF) in tropical semirings. MPF is regarded as the action of a matrix semiring on a specific matrix set. Actually, matrix power functions can be described as one-way functions due to the fact that they can be attributed to some generalized satisfiability problems that are potentially NP-complete. Machine learning is applied in combination with ZKP for achieving the prediction regarding the identity verification in information systems and better level of security.

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Issue

AIP Conference Proceedings, vol. 3182, 2025, Bulgaria, https://doi.org/10.1063/5.0246141

Copyright American Institute of Physics

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