Detection of phishing websites using C4.5 data mining algorithm

Abstract

Phishing sites are fake sites that are made by deceptive persons which are copy of genuine sites. These websites look like an official website of any company such as bank, institute, etc. The main aim of phishing is that to steal sensitive information of user such as password, username, pin number, etc. Victims of phishing attacks may uncover their money related delicate data to the attackers who may utilize this data for budgetary and criminal exercises. Different technical and non-technical approaches have been proposed to identify phishing sites. Non-Technical approach has no solution against the fast disappearance feature of phishing websites. Data mining technique, one of the classifications of technical approach, has shown promising results in detection of phishing websites. As compared to non-technical approaches, data mining techniques can generate classification models which can make prediction on phishing websites in real-time. In this paper analysis of C4.5 (J48) data mining algorithm has been done using WEKA tool. C4.5 is a benchmark data mining technique which can accurately identify phishing websites. A training dataset of 750 URLs has been made to train the algorithm J48, which is an implementation of C4.5 algorithm in WEKA. Testing dataset of 300 URLs is used to make prediction using the classifier generated after the training of J48. True positive rate, True negative rate, False positive rate, False negative rate, Success rate, Error rate and Accuracy are calculated after testing process. Result shows C4.5 has an accuracy of 82.6%. ? 2017 IEEE.