Multilayer Perceptron For Classification Of Website Phishing

Maheep Singh*, Roshni Tayal**
*-** Graduate Engineer, Department of Computer Science and Engineering, Central University, Bilaspur, Chhattisgarh, India.
Periodicity:March - May'2018
DOI : https://doi.org/10.26634/jit.7.2.14649

Abstract

Today websites are used for various purposes. There is a crime named website phishing which comes under Cybercrime. A website phishing tries to steal your account password or other private information by misleading you into believing that you're on a legitimate website. Several conventional techniques for detecting phishing websites have been suggested to cope with this problem. One could even land on a phishing site by mistyping a URL. In this study, a Multilayer Perceptron Learning approach is used after applying 10-fold cross validation as a preprocessing for website phishing classification which gives almost 100% accuracy. The experimental results show that the performance of the multilayer perceptron learning classifiers improved the results up to a greater extent.

Keywords

Website Phishing, cybercrime, Multilayer Perceptron Learning.

How to Cite this Article?

Singh,M., and Tayal,R. (2018). Multilayer Perceptron for Classification of Website Phishing. i-manager’s Journal on Information Technology, 7(2), 30-36. https://doi.org/10.26634/jit.7.2.14649

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