Generative Artificial Intelligence for Next-Generation Security Paradigms

11Machine Learning-Based Malicious Web Page Detection Using Generative AI

Ashwini Kumar¹*, Harikesh Singh², Mayank Singh² and Vimal Gupta³

¹Department of CSE, Graphic Era University, Dehradun, Uttrakhand, India

²Department of CSE (AIML), G. L. Bajaj Institute of Engineering & Technology, Greater Noida, UP, India

³Department of CSE, JSS Academy of Technical Education, Noida, UP, India

Abstract

The accelerated growth of the Internet has changed the basic ways of accessing information, communicating, shopping, and doing business by individuals and organizations. Web services have become a part of everyday life, as they help in online banking, remote work, and online shopping. However, this online convenience has also brought about bad players in the ministry. Dubious web pages are also an increasing way in which cybercriminals gain access to the system to commit phishing attacks, infect files with malware, and steal valuable information. Such pages appear as replicas of real websites and can be difficult to identify using conventional security measures. Traditional detection mechanisms, such as signature- or heuristic-based detectors, are not very effective in keeping up with the advanced and dynamic methods used by attackers. To this end, machine learning (ML) and generative AI (GenAI) seem to be effective substitutes for traditional tools. Large datasets can be learned by ML models to identify other minor trends and outliers that can be used to identify malicious actions. Meanwhile, ...