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Presenter: Jaynish Patel
Supervisor:

Date: Fri, July 27, 2018
Time: 10:00:00 - 11:00:00
Place: EOW 230

ABSTRACT

In today’s world, the internet has brought a tremendous change in e-commerce aspect of people’s lives. However, it is prone to the wide variety of security attacks. One of the most vulnerable security threat which poses a problem to the internet users is phishing. Phishing is a nontrivial problem involving deceptive emails and webpages that trick unsuspecting users into willingly revealing their confidential information. In this project, various phishing detection techniques were discussed and one technique based heuristic rule were implemented to detect the phishing URL. The different features are extracted from the given URL. The feature groups include address-bar related features, abnormal- based features, HTML – JavaScript based features and domain based features. The different heuristic rules are implemented and decision is made based on the output of the heuristic rules. Furthermore, different weightage is also assigned to each heuristic rule to detect the URL correctly.

The API id developed in Java to classified URL as phishing and Legitimate. To test the application, a dataset from Alexa and Phish tank was collected. The automated script was written, which take the URL in the JSON format and send to API running on some server and gets the Output in JSON format as Legitimate or Phishing along with the score.