A Support Vector Machine Learning Technique for Detection of Phishing Websites
Saumya Jain, Chetan Gupta
Abstract
In the field of cyber attacks, phishing is considered to be one of the pioneers. Phishing sites are websites that look and sound like legitimate ones but are really scams. For the purpose of duping the target into thinking its real, they are manufactured. The phishing scams of today are more complex and dangerous than ever before. Phishing website detection may be achieved by using machine and deep learning approaches based on artificial intelligence. It is possible to use the ML classification algorithm for phishing website detection. This paper presents a support vector machine learning technique for the detection of phishing websites. Simulation is performed using spyder IDE. Simulation results provide better accuracy.