International Journal of Advanced Research in Computer and Communication Engineering

Abstract: The rapid growth of digital infrastructure and online services has led to a significant increase in the frequency, scale, and sophistication of cyberattacks. Traditional security mechanisms such as firewalls, signature-based intrusion detection systems, and antivirus software are no longer sufficient to detect modern threats like phishing, distributed denial-of-service (DDoS) attacks, brute-force login attempts, and malicious websites. These systems often suffer from high false positives, lack of real-time analysis, and limited contextual understanding.
This paper presents CyberShield AI, an AI-powered cyber threat detection and monitoring system designed to provide real-time visibility into multiple cybersecurity threats through an integrated and interactive dashboard. The proposed system analyzes phishing emails, DDoS traffic anomalies, brute-force authentication attempts, and malicious URLs using rule-based intelligence, heuristic analysis, and AI-assisted interpretation. CyberShield AI employs a full-stack architecture with secure authentication, structured data storage, and dynamic visualizations to improve threat awareness and response time. Experimental evaluation demonstrates that the system effectively identifies and categorizes cyber threats while providing clear explanations and actionable insights, making it suitable for academic and practical cybersecurity environments.

Keywords: CyberShield AI, Cyber Threat Detection, Phishing Detection, DDoS Attack Monitoring, Brute-Force Detection, Malicious URL Analysis, Artificial Intelligence, Cybersecurity Dashboard

Downloads: | DOI: 10.17148/IJARCCE.2026.15115