Fraud Website Detection using Data Mining | Zendy

Urvashi Prajapati | Zendy; Neha Sangal | Zendy; Deepti Patole | Zendy

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Fraud Website Detection using Data Mining

Author(s) -

Urvashi Prajapati,

Neha Sangal,

Deepti Patole

Publication year - 2016

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/ijca2016909590

Subject(s) - computer science , data science , data mining , world wide web , information retrieval

Phishing attack is used to steal confidential information of user. Fraud websites appear similar to genuine websites with the logo and graphics of trusted website. Fraud Website Detection application aims to detect fraud websites using data mining techniques. This project provides intelligent solution to phishing attack. W3C standard defines characteristics which can be used to distinguish fraud and legal website. This application extracts some characteristics from URL and source code of a website. These features are used for classification. RIPPER algorithm is used to classify the websites. After classifying the websites, the application sends notification email to the administrator using WHOIS protocol. The administrator may block the fraud website after verification.

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