Intelligent rule‐based phishing websites classification. Issue 3 (1st May 2014)

• Record Type: Journal Article
• Authors: Mohammad, Rami M.; Thabtah, Fadi; McCluskey, Lee
• Is Part Of: IET information security. Volume 8:Issue 3(2014)
• Page Start: 153
• Page End: 160
• Publication Date: 2014-05-01
• Subjects: data mining -- data privacy -- pattern classification -- security of data -- unsolicited e‐mail -- Web sites; intelligent rule‐based phishing Web site classification -- Web site echoing -- creditable flrm -- user private information -- social security number -- browser‐based security indicators -- phishing attack prediction -- antiphishing solutions -- Website class -- rule‐based data mining classification techniques; Computer security -- Periodicals; Cryptography -- Periodicals; Computer networks -- Security measures -- Periodicals; Database security -- Periodicals; 005.8
• DOI: 10.1049/iet-ifs.2013.0202
• Languages: English
• ISSNs: 1751-8709

Abstract

Abstract : Phishing is described as the art of echoing a website of a creditable firm intending to grab user's private information such as usernames, passwords and social security number. Phishing websites comprise a variety of cues within its content‐parts as well as the browser‐based security indicators provided along with the website. Several solutions have been proposed to tackle phishing. Nevertheless, there is no single magic bullet that can solve this threat radically. One of the promising techniques that can be employed in predicting phishing attacks is based on data mining, particularly the 'induction of classification rules' since anti‐phishing solutions aim to predict the website class accurately and that exactly matches the data mining classification technique goals. In this study, the authors shed light on the important features that distinguish phishing websites from legitimate ones and assess how good rule‐based data mining classification techniques are in predicting phishing websites and which classification technique is proven to be more reliable.