Paper publication information
- Category: Paper publication
- Dept: INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
- Team: Shiva Kumar Nadiminti, Haritha E.
- Professor: P.Vimala Manohara Ruth.
- Paper: PREDICTION OF PHISHING WEBSITE FOR DATA SECURITY USING VARIOUS MACHINE LEARNING ALGORITHMS
- Tech-involved: Phishing, Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, XGBoost Classifier.
Prediction of Phishing Websites for Data Security Using Different Machine Learning Algorithms:
Phishing is one in all the foremost threats during this net era. Phishing may be a sensible method wherever a legitimate web site is cloned and victim’s area unit lured to the pretend web site to supply their personal yet as counselling, typically it proves to be expensive. Although most of the websites can provide a disclaimer warning to the users concerning phishing, users tend to neglect it. It is not a totally accountable action by the websites additionally and there is not a lot of that the websites might very do concerning it. Since phishing has been in persistence for an extended time, several approaches are projected in past which will find phishing websites however only a few or none of them find the target websites for these phishing attacks, accurately.
Our projected methodology tends to establish phishing websites employing a combined approach by constructing Resource Description Framework (RDF) models and mistreatment ensemble learning algorithms for the classification of internet sites. Our approach uses supervised learning techniques to coach our system. As our system explores the strength of RDF and ensemble learning ways and each these approaches work hand in hand, an extremely promising accuracy rate of 97% is achieved.