Abstract:
Users buy products online and pay via various websites.Many malicious websites request sensitive data like usernames, passwords, and credit card numbers. Phishing websites are these. We proposed an intelligent, flexible, and effective classification Data mining algorithm-based system to detect and predict phishing websites.
We classified phishing data sets using classification algorithms. The final phishing detection rate depends on URL, Domain Identity, security, and encryption criteria. Our system uses data mining algorithms to detect phishing websites when users make online payments.
E-commerce companies can secure transactions with this app. This system’s data mining algorithm outperforms other classification algorithms.
This system allows online purchases without hesitation. Admin can add phishing website url or fake website url to system to scan and add new suspicious keywords.Machine learning adds keywords to database.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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