Phishing website detection using novel machine learning fusion approach

The Phishing is a sort of social designing assault regularly used to take client information, including login accreditations and credit card numbers. With the enhancements in internet technology, websites are the major resource for the cyber-attacks. There are several counter measures available for avoiding phishing attacks, but phishers are changing their attacking methods from time to time. One of the most widely used techniques for solving cybersecurity issues is machine learning. From last several years, Machine Learning and Deep Learning Techniques are suitable for solving security related issues. Machine Learning is most suitable for detecting phishing attacks because most of the phishing attacks have common characteristics. This paper has applied several machine learning techniques for detecting the phishing attacks. Here, two prioritybased algorithms are proposed. Based on the results of these algorithms, the final fusion classifier is decided. We used a dataset from UCI and applied a novel fusion classifier and achieved an accuracy of 97%. We used Python for implementing our experiments.