EVALUATION OF CLASSIFICATION ALGORITHMS FOR PHISHING URL DETECTION

A phishing URL is a web address created with the intent of deceiving users into releasing their personal and private data or downloading malware into the users' systems without their knowledge. Increase in the adoption of the Internet has led to corresponding increase in the number of phishing...

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Bibliographic Details
Published inI-Manager's Journal on Computer Science Vol. 6; no. 3; p. 34
Main Authors OLUYOMI, AYANFEOLUWA, OLUWAFEMI, OSHO, MARYAM, SHUAIB
Format Journal Article
LanguageEnglish
Published Nagercoil iManager Publications 01.09.2018
Subjects
Algorithms
Classification
Cybersecurity
Downloading
Error analysis
Machine learning
Malware
Phishing
Root-mean-square errors
Online AccessGet full text
ISSN2347-2227
2347-6141
DOI10.26634/jcom.6.3.15698

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Summary:A phishing URL is a web address created with the intent of deceiving users into releasing their personal and private data or downloading malware into the users' systems without their knowledge. Increase in the adoption of the Internet has led to corresponding increase in the number of phishing sites globally. Many classification techniques have been developed for detecting phishing URLs. This paper seeks to evaluate the performances of existing techniques. With dataset obtained from UCI Machine Learning Repository, the algorithms were assessed in terms of Accuracy, Precision, Recall, F-Measure, Receiver Operating Characteristic (ROC) area and Root Mean Squared Error (RMSE). From analysis and comparison with results from related literature, the Random Forest was found to perform best.
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ISSN:2347-2227
2347-6141
DOI:10.26634/jcom.6.3.15698