Artificial Neural Network for Websites Classification with Phishing Characteristics

• 作者: Andréa Martiniano Dacyr Dante De Oliveira Gatto Domingos Napolitano Edquel Bueno Prado Farias Marcio Romero Renato José Sassi Ricardo Pinto Ferreira
• 来源期刊: 社交网络(英文)
• 学科: 工学
• 关键词: Artificial INTELLIGENCE Artificial Neural Network Pattern Recognition PHISHING CHARACTERISTICS SOCIAL Engineering
• 年，卷（期）: sjwlyw,（2）
• 页码范围: 97-109
• 页数: 13页
• 分类号: TP39

摘要

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.