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On the application of Explainable Artificial Intelligence (XAI) techniques for generating images from data packages to detect anomalies in computer networks

Grant number: 21/05516-1
Support Opportunities:Regular Research Grants
Duration: February 01, 2022 - January 31, 2024
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:João Paulo Papa ; Rafal Scherer


The Internet, has brought higher complexity to the Network Management area. Detecting anomalies in a network with the highest efficiency and in the shortest possible time has been the goal of many researchers, which have used Artificial Intelligence. This project aims to convert network data into images so that Convolutional Neural Networks can be used to detect deviations in network behavior. The XAI models will bring explainability and clarity to the AI algorithms used, making it possible to understand the reasons for anomalous detection or not. (AU)

Articles published in Agência FAPESP Newsletter about the research grant:
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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)
HERNANDES JUNIOR, PAULO R. GALEGO; SCHERER, RAFAL; JANUARIO, LUCAS B.; RODRIGUES, DOUGLAS; PAPA, JOAO P.; COSTA, KELTON A. P.; IEEE. From Network Package Flow to Images: How to Accurately Detect Anomalies in Computer Networks. 2022 29TH INTERNATIONAL CONFERENCE ON SYSTEMS, SIGNALS AND IMAGE PROCESSING (IWSSIP), v. N/A, p. 4-pg., . (21/05516-1, 13/07375-0, 14/12236-1, 19/07665-4)
BIAGGI, LUCAS; PAPA, JOAO P.; COSTA, KELTON A. P.; PEREIRA, DANILLO R.; PASSOS, LEANDRO A.; IEEE. FEMa-FS: Finite Element Machines for Feature Selection. 2022 26TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), v. N/A, p. 8-pg., . (21/05516-1, 17/22905-6, 13/07375-0, 16/19403-6, 14/12236-1)
MOREIRA, THIERRY P.; SANTANA, MARCOS CLEISON S.; PASSOS, LEANDRO A.; PAPA, JOAO PAULO; DA COSTA, KELTON AUGUSTO P.; PINHO, AJ; GEORGIEVA, P; TEIXEIRA, LF; SANCHEZ, JA. An End-to-End Approach for Seam Carving Detection Using Deep Neural Networks. PATTERN RECOGNITION AND IMAGE ANALYSIS (IBPRIA 2022), v. 13256, p. 11-pg., . (21/05516-1, 14/12236-1, 19/07665-4, 13/07375-0)

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