Detection of Anomalies in Large-Scale Cyberattacks Using Fuzzy Neural Networks
作者： Paulo Vitor de Campos Souza , Augusto Junio Guimarães , Thiago Silva Rezende , Vinicius Jonathan Silva Araujo , Vanessa Souza Araujo
DOI: 10.3390/AI1010005
关键词: Artificial neural network 、 Data mining 、 Anomaly detection 、 The Internet 、 Intelligent decision support system 、 Context (language use) 、 Identification (information) 、 Expert system 、 Fuzzy logic 、 Computer science
摘要: The fuzzy neural networks are hybrid structures that can act in several contexts of the pattern classification, including detection failures and anomalous behaviors. This paper discusses use an artificial intelligence model based on association between logic training to recognize anomalies transactions involved context computer cyberattacks. In addition verifying accuracy model, rules were obtained through knowledge from massive datasets form expert systems. acquired allow creation intelligent systems high-level languages with a robust level identification Internet transactions, results test confirms anomaly high-security attacks networks.
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