• Nikita Gawade
• Sayali Mundekar
• Nilam Vare
• Ruchi Gada
• Smita Bansod

Phishing sites are those sites that are designed by deceptive people to look same as legitimate sites with one or more different features which cannot be noticed by naive users. These phishing URLs seems like an original website of any organization such as bank, institutes, etc. In phishing, attacker directly attacks on user’s personal information. Phishing is a cybercrime in which victims are targeted by email, telephone or text message by stating that it is a legitimate institution to lure individuals into providing sensitive data such as personally identifiable information, banking and credit card details, and passwords. Data mining technique can be used for classification of different data which was used for detection of phishing websites as compared to non-technical approaches like blacklist-based detection techniques. Different classification algorithms can be used to predict different phishing URLs. In this paper we analyse url features using random forest algorithm to detect phishing websites. The study analyses over legitimate and phishing URLs collected from phishtank. It includes classification of different URLs using random forest classifiers .

Phishing, URL, Website, Data mining, legitimate,Random Forest.

"URL Based Analysis for Phishing Detection Using Data Mining", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 1, page no.745-747, January-2019, Available :http://www.jetir.org/papers/JETIR1901494.pdf

"URL Based Analysis for Phishing Detection Using Data Mining", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 1, page no. pp745-747, January-2019, Available at : http://www.jetir.org/papers/JETIR1901494.pdf