Its constant technological evolution characterizes the contemporary world, and every day the processes, once manual, become computerized. Data are stored in the cyberspace, and as a consequence, one must increase the concern with the security of this environment. Cyber-attacks are represented by a growing worldwide scale and are characterized as one of the significant challenges of the century. This article aims to propose a computational system based on intelligent hybrid models, which through fuzzy rules allows the construction of expert systems in cybernetic data attacks, focusing on the SQL Injection attack. The tests were performed with real bases of SQL Injection attacks on government computers, using fuzzy neural networks. According to the results obtained, the feasibility of constructing a system based on fuzzy rules, with the classification accuracy of cybernetic invasions within the margin of the standard deviation (compared to the state-of-the-art model in solving this type of problem) is real. The model helps countries prepare to protect their data networks and information systems, as well as create opportunities for expert systems to automate the identification of attacks in cyberspace.
Cyberspace, Cyber-defense, Information security, Fuzzy neural networks, SQL Injection.
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THE INTERNATIONAL JOURNAL OF FORENSIC COMPUTER SCIENCE - IJoFCS
Volume 13, Number 1, pages 8-21, DOI: 10.5769/J201801001 or http://dx.doi.org/10.5769/J201801001
Fuzzy neural networks to create an expert system for detecting attacks by SQL Injection
By Lucas Oliveira Batista, Gabriel Adriano de Silva, Vanessa Souza Araújo, Vinícius Jonathan Silva Araújo, Thiago Silva Rezende, Augusto Junio Guimarães, Paulo Vitor de Campos Souza
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