A CLIENT-SIDE COUNTER PHISHING APPLICATION USING ADAPTIVE NEURO FUZZY INFERENCE SYSTEM

Abstract

Phishing is an online scam which involves identity theft of unsuspecting users, by which an attacker steals the personal information data of users, such as user ID, password related to financial institutions such as banks, money transfer sites etc. Phishing activity takes advantage of social engineering and technological advancements, to carry out the phishing attacks. E-mails, instant messaging and webpages are used in carrying out this activity. For the success of phishing attacks, attacker disguises himself as a trusted source, such as customer care centre of a bank or stock broking firm. In this dissertation titled "A Client-Side Counter Phishing Application using Adaptive Neuro Fuzzy Inference System", a design has been proposed to detect phishing e-mails present in a user's mailbox. The application has been implemented using an intelligent hybrid technique, Adaptive Neuro-Fuzzy Inference System (ANFIS). E-mails present in a user's mailbox are first retrieved and then each one is checked for the values related to the number of occurrences of a phishing characteristics. The extracted values are fed as input to ANFIS, which gives the output corresponding to each e-mail. Thereby, warning the user regarding the presence of phishing e-mails in his mailbox. This is a preventive and proactive technique, which detects phishing activity even without opening a phishing webpage. The application has been tested and proved to be highly accurate with no false positives and negatives. A comparison with other existing anti-phishing techniques shows the better accuracy provided by the technique. iii