• Arpita Gupta
• Mahendra Patel

Data mining is one of the most essential techniques for analyzing large amount of data. The analysis of data leads to provide the data patterns by which experts can predict, make decisions and understand the associations among different attributes. Therefore, in large number of applications, the data mining techniques are frequently used. In this presented work, the data mining is demonstrated for performing the classification task of web based URLs. The main aim behind this classification is to analyze the pattern of unsolicited URLs. In this context, an accurate data mining technique namely C4.5 decision tree algorithm is used. The C4.5 decision tree algorithm is a supervised learning algorithm which performs the entire data and their attributes into a kind of tree structure and using this structure can be used for predicting the data patterns. In this decision tree, the tree nodes are providing the relationship among the data attributes and the edges of this tree provides the values of the attributes to form the relationships. Finally, the leaf node of this tree demonstrates the decision of the classification. In order to provide the decision of phishing URLs, the PhishTank data set is used. This data set contains a significant amount of phishing URLs which is further evaluated on the basis of feature extraction technique. Using these feature study and obtained patterns in data, the decision tree algorithm is prepared and prediction is made. In order to justify the performance of the proposed URL classification technique. A traditional technique is also implemented which is based on Apriori algorithm. The comparative performance study demonstrates the proposed technique is efficient and accurate as compared to the Apriori based phishing URL classification technique.

Data Mining, Phishing, URL Detection, Decision Tree, Apriori, PhishTank, Phishing Website.

"Applying C4.5 Decision Tree to Classify Phishing URL", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 9, page no.339-345, September-2018, Available :http://www.jetir.org/papers/JETIR1809556.pdf

"Applying C4.5 Decision Tree to Classify Phishing URL", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 9, page no. pp339-345, September-2018, Available at : http://www.jetir.org/papers/JETIR1809556.pdf