• Shubham Sudhir Walde
• Piyush Sunil Katkar
• Sneha Sagar Waghmare
• Snehal Krishna Dhapodkar
• Aishwarya Daduji Badole

Phishing scam is known unlawful activity in which victims are defraud to disclose the confidential data and information specially related to user personal financial information. There are various phishing schemes such as deceptive, malware based, DNS-based, etc. Hence in this paper, a systematic review analysis on existing works related with the phishing detection and response techniques together with apoptosis have been further investigated and evaluated. Phishing is a significant problem involving fraud email and web sites that mislead unsuspecting users into disclosing private information. In this paper, we present the design, implementation, and evaluation of various techniques for detecting phishing web sites. Phishing websites are fake websites that are created by dishonest people to mimic web pages of real websites. Victims of phishing attacks may expose their financial sensitive information to the attacker whom might use this information for financial and criminal activities. This paper investigates features selection aiming to determine the effective set of features in terms of classification performance.

Keywords: CANTINA, Data Mining, phishing websites, Security, website security.

"Detecting Phishing Website using Associative Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 2, page no.210-213, February-2018, Available :http://www.jetir.org/papers/JETIR1802030.pdf

"Detecting Phishing Website using Associative Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 2, page no. pp210-213, February-2018, Available at : http://www.jetir.org/papers/JETIR1802030.pdf