Visible to the public Applying Machine Learning Techniques to Detect and Analyze Web Phishing Attacks

TitleApplying Machine Learning Techniques to Detect and Analyze Web Phishing Attacks
Publication TypeConference Paper
Year of Publication2018
AuthorsCuzzocrea, Alfredo, Martinelli, Fabio, Mercaldo, Francesco
Conference NameProceedings of the 20th International Conference on Information Integration and Web-Based Applications & Services
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-6479-9
KeywordsHuman Behavior, human factor, phishing, pubcrawl
Abstract

Phishing is a technique aimed to imitate an official websites of any company such as banks, institutes, etc. The purpose of phishing is to theft private and sensitive credentials of users such as password, username or PIN. Phishing detection is a technique to deal with this kind of malicious activity. In this paper we propose a method able to discriminate between web pages aimed to perform phishing attacks and legitimate ones. We exploit state of the art machine learning algorithms in order to build models using indicators that are able to detect phishing activities.

URLhttps://dl.acm.org/doi/10.1145/3282373.3282422
DOI10.1145/3282373.3282422
Citation Keycuzzocrea_applying_2018