Phishing detection using RDF and random forests
Joint Authors
Muppavarapu, Vamsee
Rajendran, Archanaa
Vasudevan, Shriram
Source
The International Arab Journal of Information Technology
Issue
Vol. 15, Issue 5 (30 Sep. 2018), pp.817-824, 8 p.
Publisher
Publication Date
2018-09-30
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
Phishing is one of the major threats in this internet era.
Phishing is a smart process where a legitimate website is cloned and victims are lured to the fake website to provide their personal as well as confidential information, sometimes it proves to be costly.
Though most of the websites will give a disclaimer warning to the users about phishing, users tend to neglect it.
It is not a fully responsible action by the websites also and there is not much that the websites could really do about it.
Since phishing has been in persistence for a long time, many approaches have been proposed in past that can detect phishing websites but very few or none of them detect the target websites for these phishing attacks, accurately.
Our proposed method is novel and an extension to our previous work, where we identify phishing websites using a combined approach by constructing Resource Description Framework (RDF) models and using ensemble learning algorithms for the classification of websites.
Our approach uses supervised learning techniques to train our system.
This approach has a promising true positive rate of 98.8%, which is definitely appreciable.
As we have used random forest classifier that can handle missing values in dataset, we were able to reduce the false positive rate of the system to an extent of 1.5%.
As our system explores the strength of RDF and ensemble learning methods and both these approaches work hand in hand, a highly promising accuracy rate of 98.68% is achieved
American Psychological Association (APA)
Muppavarapu, Vamsee& Rajendran, Archanaa& Vasudevan, Shriram. 2018. Phishing detection using RDF and random forests. The International Arab Journal of Information Technology،Vol. 15, no. 5, pp.817-824.
https://search.emarefa.net/detail/BIM-839133
Modern Language Association (MLA)
Muppavarapu, Vamsee…[et al.]. Phishing detection using RDF and random forests. The International Arab Journal of Information Technology Vol. 15, no. 5 (Sep. 2018), pp.817-824.
https://search.emarefa.net/detail/BIM-839133
American Medical Association (AMA)
Muppavarapu, Vamsee& Rajendran, Archanaa& Vasudevan, Shriram. Phishing detection using RDF and random forests. The International Arab Journal of Information Technology. 2018. Vol. 15, no. 5, pp.817-824.
https://search.emarefa.net/detail/BIM-839133
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 823-824
Record ID
BIM-839133