A SURVEY ON PREDICTION OF PHISHING WEBSITE USING MACHINE LEARNING TECHNIQUE









Abstract

The Internet has become an integral part of our lives, it has also provided opportunities for malicious activities such as phishing to be performed out anonymously. Phishers utilise bogus websites to deceive users and steal account information such as usernames, passwords, and account IDs from individuals and corporations. Despite the development of various detection systems for phishing websites, phishers have modified their ways to prevent detection. One of the most efficient methods for recognising this violent act is machine learning. Because the majority of phishing assaults have some characteristics that machine learning techniques can identify. In this article, we examined the performance of several machine learning algorithms for identifying phishing websites. The various new techniques, specificity, accuracy and f-score of phishing are surveyed. In the survey, recent research area publication of phishing are analysed. Finally, some related issues, challenges and solution for phishing are also discussed.


Modules


Algorithms


Software And Hardware