© 2020 JETIR June 2020, Volume 7, Issue 6 www.jetir.org (ISSN-2349-5162) JETIR2006537 Journal of Emerging Technologies and Innovative Research (JETIR) www.jetir.org 1410 Webpage Classification for Detecting Phishing Attack 1 Omejevwe Efe-odenema, 2 Dr. Jitendra Jaiswal 1 Student, 2 Associate Professor, 1Department of Computer Science and technology, Jain (Deemed to be University), Bengaluru, India. Abstract: Despite numerous research efforts, phishing attacks remain prevalent and highly effective in luring unsuspecting users to reveal sensitive information, including account credentials and social security numbers. In this paper, we propose the use of three machine algorithm to help in the detection of phishing attacks. Machine learning algorithm has been popular over the years for implementing and solving different problems. Different features were observed and approximately 112 features were used from 88,648 dataset, gotten from Vrbancic UC Machine Learning Repository database. Through the use the algorithms, high accuracy were gotten especially after the application of PCA feature selection. IndexTerms - principal component analysis, Machine Learning Framework. I. INTRODUCTION Recent advances in technology, which have to enable online users to have a better experience while carrying out their day to day activities with ease, this has also created an avenue for criminals to carry out their illegal activities. One of the most recent of them is the phishing attack. This is done by stealing private information both personal identity data and financial account credentials such as credit card details, password to carry out fraudulent activities. The attacker usually does this by using a phishing URL and an email to deceive users. Phishing employs the use of social engineering to fool users that they are dealing with a legitimate source. They lead the user into phish websites into divulging financial details.[1] There has been recent trend according to Phishing Activity Trends Report, during the first quarter of 2020, during the time of COVID-19, cybercriminals launched numerous attacks relating to COVID-19 as they launched phishing and malware attacks on health workers, healthcare facilities and recently unemployed as they were vulnerable, having just lost their means of livelihood. There was a slight increase in phishing attacks. [2]Recorded that 165,772 attacks took place as against 162,155 as of the end of the 4th quarter of 2019. A new trend was discovered as most phishing website now uses an SSL certificate for security, this makes a phishing attack more cumbersome to curb. Phishing targeting webmail and software as a service user continued as the biggest category of phishing. Zoom technology, an online platform that is used by business owners for meetings was used by the Cybercriminal to carry out crime during the pandemic by creating fake video-conferencing meetings, leading the user into a fake website where their credential was stolen. The figure below shows the statistic and trends of phishing attack in the first quarter of 2020. January February March Number of unique phishing Web sites detected 54,926 49,560 60,286 Number of unique phishing e-mail reports (campaigns) received by APWG from consumers 52,407 43,270 44,008 Number of brands targeted by phishing campaigns 374 331 344 fig. 1.1 statistical highlights for 1st quarter 2020