ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774

ILLEGITIMATE WEBSITES DETECTION USING DEEPLEARNING FRAMEWORK

Abstract

Abstract: Phishing is a crime involving robbery of confidential user data. The phishing websites are aimed at individuals,businesses, and cloud storage and government websites. Hardware- based anti-phishing methods are generally used, butsoftware- based approaches are favored because of costs and operational factors. There is no solution to the problem such aszero-day phishing attacks from current phishing detection approaches. A three-phase attack detection called the PhishingAttack Detector based on Web Crawler was proposed to resolve these problems and precisely detect phishing incidences usingrecurrent neural network. It includes the input features Web traffic, web content and Uniform Resource Locator (URL) basedon the classification of phishing and non-phishing pages.Keywords: —Recurrent Neural Network, Deep Learning, illegitimate URLs, cyberattacks

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