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International Journal of Computer Engineering in Research Trends. Scholarly, Peer-Reviewed, Open Access and Multidisciplinary

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Phishing Urls Detection Using Machine Learning Techniques

Sushma Joshi, Dr S.M Joshi, , ,
Affiliations
Computer Science and Engineering, SDM College of Engineering and Technology, Visveswaraya Technological University, Dharwad, India
:10.22362/ijcert/2019/v6/i06/v6i0602


Abstract
Phishing is an attempt to get any sensitive information like user identity information, banking details and passwords from target or targets which is considered as fraudulent attack. Phishing causes huge loss to the internet users every year. It is a captivating technique used obtain all the personal and financial information from the pool users of internet. This project deals with the methodologies of identifying the phishing websites with the help of machine leaning algorithms. We have considered the lexical properties, host based and page-based properties of the URLs which are used for identifying the phishing URLs. Various Machine learning algorithms are implemented for feature evaluation of the URLs which have widespread phishing properties. These website properties are refined so that a best suitable classifier tis identified which can distinguish between benign and phishing site.


Citation
Sushma Joshi,Dr S.M Joshi."Phishing Urls Detection Using Machine Learning Techniques". International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084 ,Vol.6, Issue 06, June - 2019, URL :326-333,


Keywords : URL, phishing, benign, legitimate, malicious.

References
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[2]	J. Ma, L. K. Saul, S. Savage and G. M. Voelker,” Beyond Blacklists: Learning to Detect Phishing Web Sites from Suspicious URLs”, Proc.of SIGKDD '09
[3]	J. Ma, L. K. Saul, S. Savage, and G. M. Voelker,” Learning to Detect Phishing URLs”, ACM Transactions on intelligent Systems and Technology, Vol. 2, No.3, Article 30, Publication date: April 2011.
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[12]	Mohammad Fazli Baharuddin, Tengku Adil Tengku Izhar, Mohd Shamsul Mohd Shoid “Malicious Url Classification System Using Multi-Layer Perceptron Technique”, In proceedings of the Journal of Theoretical and Applied Information Technology.


DOI Link : https://doi.org/10.22362/ijcert/2019/v6/i06/v6i0602

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DOI:10.22362/ijcert


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