Intelligent Rule based Phishing Websites Classification
Abstract
Phishing
is described as the art of emulating 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 browser-based
security indicators. 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 used
in predicting phishing attacks is based on data mining. Particularly the
“induction of classification rules”, since anti-phishing solutions aim
to predict the website type accurately and these exactly fit the
classification data mining. In this paper, we shed light on the
important features that distinguish phishing websites from legitimate
ones and assess how rule-based classification data mining techniques are
applicable in predicting phishing websites. We also experimentally show
the ideal rule based classification technique for detecting phishing.
You download the full article from the following link:
No comments:
Post a Comment