TITLE:
Artificial Neural Network for Websites Classification with Phishing Characteristics
AUTHORS:
Ricardo Pinto Ferreira, Andréa Martiniano, Domingos Napolitano, Marcio Romero, Dacyr Dante De Oliveira Gatto, Edquel Bueno Prado Farias, Renato José Sassi
KEYWORDS:
Artificial Intelligence, Artificial Neural Network, Pattern Recognition, Phishing Characteristics, Social Engineering
JOURNAL NAME:
Social Networking,
Vol.7 No.2,
April
27,
2018
ABSTRACT: Several threats are propagated by malicious websites largely classified as phishing. Its function is important information for users with the purpose of criminal practice. In summary, phishing is a technique used on the Internet by criminals for online fraud. The Artificial Neural Networks (ANN) are computational models inspired by the structure of the brain and aim to simu-late human behavior, such as learning, association, generalization and ab-straction when subjected to training. In this paper, an ANN Multilayer Per-ceptron (MLP) type was applied for websites classification with phishing cha-racteristics. The results obtained encourage the application of an ANN-MLP in the classification of websites with phishing characteristics.