Quantum Intelligent Systems for Cybersecurity

• Grant number: 23/12830-0
• Support Opportunities: Regular Research Grants
• Start date: May 01, 2024
• End date: April 30, 2026
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Kelton Augusto Pontara da Costa
• Grantee: Kelton Augusto Pontara da Costa
• Host Institution: Faculdade de Ciências (FC). Universidade Estadual Paulista (UNESP). Campus de Bauru. Bauru , SP, Brazil
• Associated researchers: Felipe Fernandes Fanchini ; João Paulo Papa ; Rafal Scherer
• Associated scholarship(s): 24/14934-0 - Quantum Machine Learning in Anomaly Detection: Benchmarking, Noise Mitigation and Applications., BP.PD; 24/18453-6 - Quantum Intelligent Systems for Cybersecurity, BP.TT

Abstract

The growth in the use of Data Networks, such as the Internet, brought greater complexity to the area of network management. Detecting anomalies in a network, with greater effectiveness and in the shortest possible time, has been the objective of many researchers using Artificial Intelligence. Thus, the research project in question proposes the investigation of intelligent quantum systems and algorithms for detecting anomalies in computer networks, since quantum computing, through some algorithms, has shown excellent results for problems such as factoring and search optimizations. Quantum computing uses some physical phenomena that break our logical and classical understanding. It is precisely from these phenomena that quantum computing manages to overcome classical computing in solving specific problems. This proposal aims to present a study on detecting network anomalies by transforming network data into images. These images will be used to detect anomalies using Artificial Neural Networks (ANN), with the support of Explainable Artificial Intelligence XAI techniques, through Quantum Machine Learning (QML) algorithms, the principal and unprecedented contribution to uniting XAI, Quantum Computing, and Network Packet Conversion in images to detect anomalies. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

BARRETO, ARTUR GOMES; FANCHINI, FELIPE FERNANDES; PAPA, JOAO PAULO; ALBUQUERQUE, VICTOR HUGO C. DE. Why consider quantum instead classical pattern recognition techniques?. APPLIED SOFT COMPUTING, v. 165, p. 11-pg., 2024-08-21. (23/14427-8, 23/04987-6, 13/07375-0, 23/12830-0)