DEVELOPMENT OF A MACHINE LEARNING MODEL FOR EARLY DETECTION OF MALICIOUS WEB ATTACKS IN INFORMATION SYSTEMS

Abstract

The rapid expansion of web-based information systems has significantly increased the exposure of organizations and users to cyber threats. Malicious web attacks such as phishing, SQL injection, cross-site scripting (XSS), malware injection, and distributed denial-of-service (DDoS) attacks have become more sophisticated and difficult to detect using traditional signature-based security mechanisms.