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DNS and semantic analysis for phishing detection

Abstract : Phishing is a kind of modern swindles that targets electronic communications users and aims to persuade them to perform actions for a another’s benefit. Phishing attacks rely mostly on social engineering and that most phishing vectors leverage directing links represented by domain names and URLs, we introduce new solutions to cope with phishing. These solutions rely on the lexical and semantic analysis of the composition of domain names and URLs. Both of these resource pointers are created and obfuscated by phishers to trap their victims. Hence, we demonstrate in this document that phishing domain names and URLs present similarities in their lexical and semantic composition that are different form legitimate domain names and URLs composition. We use this characteristic to build models representing the composition of phishing URLs and domain names using machine learning techniques and natural language processing models. The built models are used for several applications such as the identification of phishing domain names and phishing URLs, the rating of phishing URLs and the prediction of domain names used in phishing attacks. All the introduced techniques are assessed on ground truth data and show their efficiency by meeting speed, coverage and reliability requirements. This document shows that the use of lexical and semantic analysis can be applied to domain names and URLs and that this application is relevant to detect phishing attacks
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Submitted on : Thursday, March 29, 2018 - 1:24:38 PM
Last modification on : Saturday, October 16, 2021 - 11:26:09 AM


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  • HAL Id : tel-01751692, version 1



Samuel Marchal. DNS and semantic analysis for phishing detection. Other [cs.OH]. Université de Lorraine, 2015. English. ⟨NNT : 2015LORR0058⟩. ⟨tel-01751692⟩



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