Analysis of Machine Learning Algorithms to Protect from Phishing in Web Data Mining

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 159 - Number 1
Year of Publication: 2017
Authors:
N. Swapna Goud
10.5120/ijca2017912743

Swapna N Goud. Analysis of Machine Learning Algorithms to Protect from Phishing in Web Data Mining. International Journal of Computer Applications 159(1):30-34, February 2017. BibTeX

@article{10.5120/ijca2017912743,
	author = {N. Swapna Goud},
	title = {Analysis of Machine Learning Algorithms to Protect from Phishing in Web Data Mining},
	journal = {International Journal of Computer Applications},
	issue_date = {February 2017},
	volume = {159},
	number = {1},
	month = {Feb},
	year = {2017},
	issn = {0975-8887},
	pages = {30-34},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume159/number1/26969-2017912743},
	doi = {10.5120/ijca2017912743},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

The term Big data is a large data sets those outgrow the simple kind of database and data handling design. We designed prototype of website phishing detection solution to address the requirements for both effective and efficient phishing detection machine learning big data allows us to dig into a tremendous amount of data that fix the problem and extract predictive signals for the phishing problem. As the cyber security problems grows many types of phishing activities may arises bid data analytics is pretty helpful in identifying various phishing threats of suppliers by scanning various data roots such as personal contacts service level agreements exploring various unstructured data sources log reports and big data analysis highly suitable for analyzing. Our research work presents big data analytics that aims to prevent malicious email notifications & phishing from web service

References

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Keywords

Phishing, Cybercrime, Big Data, Webservice, Emails