Phishing Website Detection Using Ensemble Technique |
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<--International Journal of Computer Trends and Technology (IJCTT)--> | 
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| © 2021 by IJCTT Journal | ||
| Volume-69 Issue-3 |
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| Year of Publication : 2021 | ||
| Authors : Priyanka Sharma, Rajni Ranjan Singh Makwana | ||
| DOI : 10.14445/22312803/IJCTT-V69I3P106 | ||
How to Cite?
Priyanka Sharma, Rajni Ranjan Singh Makwana, "Phishing Website Detection Using Ensemble Technique," International Journal of Computer Trends and Technology, vol. 69, no. 3, pp. 26-29, 2021. Crossref, 10.14445/22312803/IJCTT-V69I3P106
Abstract
In the age of the internet, there is an enormous number of online transactions performed every day; therefore security and privacy of online transactions and banking websites is a challenging task. Website phishing attacks are carried out by presenting a fake website as a genuine one in order to gain confidential information and using that for some non-genuine activities. In this work, the Bagging technique is used with neural network and LMT classifiers as base classifiers in ensemble to classify a set of URLs and to determine the URLs as phishing or legitimate so that a user can be secured from phishing attacks. In this work, we have obtained an accuracy of 90%.
Reference
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Keywords
Phishing detection, Ensemble classifiers, Classification techniques, Internet security, Machine Learning.