A Novel Approach for Phishing URLs Detection using Naïve Bayes, Neural Network and Random Forest Classifiers

Journal

International Journal of Digital Applications and Contemporary Research (IJDACR)

ISSN

2319-4863

Volume / Issue

Vol.5 · Issue 4

Published

November 2016

Access

Open Access

Licence

CC BY-NC-SA 4.0

Gangeshwari Sharma Abhishek Tiwari

Seeking sensitive user data in the form of online banking user - id and passwords or credit card information, which may then be used by ‘ phishers ’ for their own personal gain is the primary objective of the phishing e - mails. With the increase in the online trading activities, there has been a phenomenal increase in the phishing scams which have now started achieving monstrous proportions . This paper gives strategies for distinguishing phishing sites by d issecting different components of phishing URLs by Machine learning systems. It talks about the systems utilized for identification of phishing sites in view of lexical features, host properties and page significance properties. We consider different machi ne learning algorithms for assessment of the features to show signs of improvement comprehension of the structure of URLs that spread phishing. We use Naïve Bayes, Neural Network and Random Forest Classifiers .

Gangeshwari Sharma, Abhishek Tiwari (2016). A Novel Approach for Phishing URLs Detection using Naïve Bayes, Neural Network and Random Forest Classifiers. International Journal of Digital Applications and Contemporary Research (IJDACR), Vol.5, Issue 4. ISSN: 2319-4863.

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