Over the years, the Internet has overwhelmed humankind and increased the dependence of human civilization on it. With the rising number of users, the Internet has become the primary source of security threats to computing systems. These computing systems, viz., computers, mobiles, and now IoT devices, have proliferated in the past decade. Amongst these, mobiles have become nearly ubiquitous with human existence. With the number of people browsing the Internet increasing exponentially, webbased attacks have become the most preferred means of attack. Security firms are now trying to battle these web-based attacks. However, these attacks are evolving rapidly, making it difficult for previous generations of security solutions to keep pace with them. Developed suitable deep learning models to predict malicious webpages using both structured and raw data as input. It has used both supervised and unsupervised approaches for producing these deep learning models. Using state-of-the-art techniques, these Deep learning models have surpassed previous performance metrics

Deep Learning, Web Page, Web Security, Learning Model