IDENTIFICATION OF URL BASED ATTACKS FROM IP DATA

The “Identification of URL-Based Attacks from IP Data” project represents a significant advancement in cybersecurity by shifting from conventional, reactive defenses to a proactive, data-driven framework. By integrating IP address intelligence, the system adds a vital contextual layer—such as geolocation, ASN reputation, and hosting provider data than traditional URL-only analysis. Leveraging advanced machine learning and deep learning, the system continuously adapts to evolving attack strategies, ensuring high resilience against zero-day attacks that often bypass static, rule-based filters. Its real-time processing and scalable cloud architecture make it a practical solution for any environment, from small businesses to largeenterprises. The study clearly shows how AI and data science can effectively solve real-world security challenges, assisting organizations in minimizing economic impact and safeguarding reputation, while contributing to a safer online ecosystem.

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