Applying Machine Learning Techniques to Detect and Analyze Web Phishing Attacks
Title | Applying Machine Learning Techniques to Detect and Analyze Web Phishing Attacks |
Publication Type | Conference Paper |
Year of Publication | 2018 |
Authors | Cuzzocrea, Alfredo, Martinelli, Fabio, Mercaldo, Francesco |
Conference Name | Proceedings of the 20th International Conference on Information Integration and Web-Based Applications & Services |
Publisher | ACM |
Conference Location | New York, NY, USA |
ISBN Number | 978-1-4503-6479-9 |
Keywords | Human 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. |
URL | https://dl.acm.org/doi/10.1145/3282373.3282422 |
DOI | 10.1145/3282373.3282422 |
Citation Key | cuzzocrea_applying_2018 |