Data and knowledge management in industrial-scale tasks using quantum technologies

The complexity of optimization tasks to ensure the quantum resilience of information systems is exponential in time. Modern computers are not able to find an accurate solution to such problems for practically relevant dimensions in a reasonable time. One of the possible ways to solve this problem is to create and use machines based on various physical principles specifically designed to solve optimization problems. In this doklad, it is proposed to use the quantum annealing method and the extended Potts model to solve these problems. It is argued that the effectiveness of quantum algorithms is related to the features of the energy profile structure, such as the presence of regions with a high density of local minima in the thermodynamic limit. The optimization problem is presented in the form of a quadratic binary optimization problem without constraints (QUBO), or in an equivalent form – in the form of the Ising problem. This allows us to determine the global minima of the energy landscape, reflecting the behavior of information systems under the conditions of quantum attacks by Shor and Grover and their well-known modifications, as well as optimal self-healing processes of the mentioned information systems, preventing their transition to irreversible catastrophic states.

The talk will be given in Russian.

Sergei A. Petrenko

Sergei A. Petrenko is a Professor and the Head of the Information Security Center at Innopolis University. Previously, he worked as a Director of the Center of Cybersecurity Systems JSFC Sistema, and designed integrated security systems, including three national control centers, two trusted MVNO service providers, five computer security incident response centers (CERT/CSIRT), https://www.adscientificindex.com/scientist/sergei-petrenko/4361100.