• Gentem Varaprasd
• K Shalivahana Reddy

Phishing is a method of trying to gather personal information using deceptive e-mails and websites. Phishing is a cyber attack that uses disguised email as a weapon. The goal is to trick the email recipient into believing that the message is something they want or need — a request from their bank, for instance, or a note from someone in their company — and to click a link or download an attachment. Phishers use the websites which are visually and semantically similar to those real websites. Machine learning is a powerful tool used to strive against phishing attacks. In this paper discuss an efficient approach to detect phishing websites using supervised machine learning algorithm. In this paper, we propose a classification model in order to classify the phishing attacks. This model comprises of feature extraction from sites and classification of website.

Phishing website, Supervised Machine Learning, Decision Tree, Phishing, Phishing Websites, Detection, Machine Learning.

"An Efficient approach for Detecting Phishing Websites Using Supervised Machine Learning Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 11, page no.672-678, November-2018, Available :http://www.jetir.org/papers/JETIR1811B99.pdf

"An Efficient approach for Detecting Phishing Websites Using Supervised Machine Learning Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 11, page no. pp672-678, November-2018, Available at : http://www.jetir.org/papers/JETIR1811B99.pdf