Models and Methods for Information Security Management: Quantum Computing and the Deutsch–Jozsa Algorithm

Abstract In the field of quantum computing, the Deutsch–Jozsa problem serves as a classical example illustrating the computational advantages of quantum algorithms over classical counterparts in specific scenarios. The problem involves efficiently determining the nature of a multi-valued function, showcasing how quantum parallelism can accelerate problem-solving. The Deutsch–Jozsa algorithm provides a framework for exploring these quantum advantages and offers insights into optimization tasks such as the minimum spanning tree (MST) problem in network design. Applications include network engineering, routing optimization, and resource allocation, where quantum-enhanced approaches can potentially outperform classical methods. This study examines the implementation of the Deutsch–Jozsa algorithm on quantum simulators and its adaptation in quantum versions of classical MST algorithms, such as the Ambainis–Spalek quantum variant of Edmonds–Karp. The analysis highlights the role of Grover’s search as a foundational component, integrating it with quantum MST techniques. Practical simulations using IBM Quantum platforms illustrate the algorithm’s potential for network optimization and broader information security applications.