A Machine Learning Approach for Detection of Phished Websites Using Neural Networks

Main Article Content

Charmi J. Chandan, Hiral P. Chheda, Disha M. Gosar, Hetal R. Shah, Prof. Uday Bhave.

Abstract

Phishing is a means of obtaining confidential information through fraudulent website that appear to be legitimate .On detection of all the criteria ambiguities and certain considerations involve hence neural network techniques are used to build an effective tool in identifying phished websites There are many phishing detection techniques available, but a central problem is that web browsers rely on a black list of known phishing website, but some phishing website has a lifespan as short as a few hours. These website with a shorter lifespan are known as zero day phishing website. Thus, a faster recognition system needs to be developed for the web browser to identify zero day phishing website. To develop a faster recognition system, a neural network technique is used which reduces the error and increases the performance. This paper describes a framework to better classify and predict the phishing sites.

Article Details

How to Cite
, C. J. C. H. P. C. D. M. G. H. R. S. P. U. B. (2014). A Machine Learning Approach for Detection of Phished Websites Using Neural Networks. International Journal on Recent and Innovation Trends in Computing and Communication, 2(12), 4205–4209. https://doi.org/10.17762/ijritcc.v2i12.3639
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Articles