Phishing Urls Detection System Using Lexical Feature Analysis - Dr. K. Vijaya Kumar, Ms. Y. Vineela Sravya and Mrs.J.Himabindu, (International Journal of Advanced Science and Technology, 2020)
Phishing website aims to steal your account password or any other confidential data by making youto believing that you’re on a legitimate website. You can even land on a phishing website by clickingon suspicious URL. These URLs are called malicious URLs. The inability of the end user system todetect and remove the malicious URLs can put the legitimate user in vulnerable condition. There arenumber of solutions to identify phishing websites have been proposed. These methods fetch websitecontent which results in undesired side effects. Also there are solutions like black-listing. Blacklisting contains the list of all URLs which are previously known to be malicious. But the list is not upto-date and also it is a time consuming task. To overcome this problem, a classification model isdeveloped to identify these dynamically changing URLs. In this paper we present a model which isbuilt using lexical feature analysis that not only takes care about syntactical nature of the URL, butalso the type of attack which the URL is undergone. The type of attack is determined based on thekeywords present in the URL. Moreover, the frequency of a particular type of attack is specified, sothat we can identify which type of attack that we are highly facing by the use of generic framework.And hence user can take the preventive measures by providing more security against frequentattacks. For better analysing, we presented a graphical visualization on the frequency of attacks.