Abstract: A Phishing is one of the most potentially disruptive actions that can be performed on the Internet. Phishing sends malicious links or attachments through emails that can perform various functions, including capturing the victim's login credentials or account information. It is a form of identity theft, in which criminals build replicas of target websites and lure unsuspecting victims to disclose their sensitive information like passwords, PIN, etc. It is one of the social engineering methods that gathers personal information through malicious websites and deceptive e-mail to canvass personal information from a company or an individual [5]. In terms of website interface and uniform resource locator (URL), most phishing webpages look identical to the actual webpages. Various strategies for detecting phishing websites, such as blacklist, heuristic, Etc., have been suggested. There is a demand for an intelligent technique to protect users from the cyber-attacks. In this study, we are trying to propose a URL detection technique based on Machine learning approaches. Boosting method is employed to detect phishing URL.

Keywords: Anti-phishing, Phishing types, Phishing websites, Phishing detection techniques, Cyber security, Machine learning classifiers.

| DOI: 10.17148/IARJSET.2022.9340