Abstract: Web phishing is a social engineering cyber attack that is used to gain the credentials of a legitimate user to achieve unauthorized access to the victim’s account using stolen credentials. Most of the phishing attacks happen on social media, E-commerce, net banking, and mobile platforms. Phishing website is one of the internet security problems that target human vulnerabilities rather than software vulnerabilities. Here, we improve the accuracy of the results. It aims to prevent online fraud and protect internet users from falling prey to phishing attacks. The project involves developing an automated system that can identify and flag websites that attempt to deceive users into divulging sensitive information such as login credentials, credit card details, and personal data. The backend signature detection approach is based on machine learning algorithms that are trained to identify the patterns and characteristics of phishing websites. The system uses these algorithms to compare the identified websites against a database of known phishing sites and to determine the likelihood that a particular site is attempting to deceive users. Overall, the Web Phishing Detection Based on Web Crawling and Backend Signature project is an important step towards improving online security and protecting users from the growing threat of phishing attacks.
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DOI:
10.17148/IJARCCE.2023.12513
