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PhishScore: Hacking Phishers' Minds

Abstract : Despite the growth of prevention techniques, phishing remains an important threat since the principal countermeasures in use are still based on reactive URL blacklisting. This technique is inefficient due to the short lifetime of phishing Web sites, making recent approaches relying on real-time or proactive phishing URLs detection techniques more appropriate. In this paper we introduce PhishScore, an automated real-time phishing detection system. We observed that phishing URLs usually have few relationships between the part of the URL that must be registered (upper level domain) and the remaining part of the URL (low level domain, path, query). Hence, we define this concept as intra-URL relatedness and evaluate it using features extracted from words that compose a URL based on query data from Google and Yahoo search engines. These features are then used in machine learning based classification to detect phishing URLs from a real dataset.
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Contributor : Jérôme François Connect in order to contact the contributor
Submitted on : Thursday, December 11, 2014 - 9:58:10 PM
Last modification on : Saturday, June 25, 2022 - 7:41:42 PM


  • HAL Id : hal-01094238, version 1



Samuel Marchal, Jérôme François, Radu State, Thomas Engel. PhishScore: Hacking Phishers' Minds. International Conference on Network and Service Management, Nov 2014, Rio de Janeiro, Brazil. ⟨hal-01094238⟩



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