PREVENTION OF PHISIHING

Abstract

Phishing is a common cyberattack in which fake websites are used to deceive individuals into revealing their personal information. Phishing URLs and fraudulent webpages are often designed to steal sensitive data such as usernames, passwords, and online banking details. Attackers create websites that visually and structurally resemble legitimate websites in order to trick users into trusting them. As technology has advanced, phishing techniques have also become more sophisticated, making it increasingly difficult for users to identify such threats. To address this issue, anti-phishing systems can be developed to detect and prevent phishing attacks. Machine learning has emerged as a powerful approach for identifying phishing activities by analyzing patterns and characteristics of suspicious URLs and websites. The proposed system explores the use of machine learning techniques to improve the detection of phishing attacks. By studying different features of web links and webpage structures, the system aims to accurately identify phishing websites and help protect users from potential cyber threats