Published Paper Details:

Phishing attacks are a type of cybercrime that are made successful by malware and social engineering. It is a serious danger that must be accepted by everyone and everything. Uniform Resource Locators (URLs), sometimes referred to as web links, are the mechanism by which people search the internet for particular pages. The analysis educates readers about phishing, shows them how to spot phishing attempts, and inspires them to take preventative measures. Phishers trick their victims by sending emails or messages that contain links to dangerous websites (known as "phishing" or "spear phishing"). Businesses and individuals are unable to identify all of the phishing emails and messages that are sent to them because of the sheer number that they receive daily. We explore numerous machine learning techniques for phishing attack detection in this section. It is used here to determine whether a particular group of links is a phishing effort or not. Phishing is a common strategy used by cybercriminals to deceive victims into providing personal information. Phishing web addresses are intended to steal sensitive information such as login passwords and financial data from unwary users. Phishing websites can sometimes closely mimic authentic ones, both visually and philosophically. Anti-phishing technologies are required because phishing attempts are becoming more sophisticated as technology advances. Machine learning has emerged as a powerful tool in the fight against phishing. This study gives an in-depth look at machine learning detection techniques and the features they employ.