SI-BBA – A novel phishing website detection based on Swarm intelligence with deep learning

Websites phishing is one of several defense coercions to Internet Service Provider. Mainly web phishing focused on stealing private information such as username, password, and credit card details too through imitating a legal creature. Deep learning based Neural Networks are extensively used for phishing detection with high accuracy measures and metrics. In this proposed work, an improved version of Binary Bat namely Swarm Intelligence Binary Bat Algorithm is used for designing the neural network which categorize the network URL websites similar to classification approach. It is utilized for the initial moment in this domain of relevance to the preeminent of our understanding. Our experimental results shows that deep learning based Adam optimizer reaches high classification accuracy as 94.8% in phishing websites attack detection based on swarm intelligence technique.