Summary:

• Increasing cyber threats in cloud environments call for enhanced security measures.
• This paper explores an AI-powered system encompassing network traffic classification, web intrusion detection, and malware analysis.
• It large-scale deployment is facilitated by modern cloud services such as Google Cloud and Microsoft Azure.

Key Findings:

• The Random Forest model successfully classified cyber threats with 90% accuracy.
• Deep learning enhancements brought precision to the system while maintaining efficiency using GPUs.
• The implementation on cloud services not only aids the scalability but also ensures robust and efficient responses to cyber incidents.

Opinion:

• The development of AI-led systems underscores the critical role of machine learning in strengthening our cybersecurity frameworks.
• The study underlines the importance of integrating AI with established cloud technologies for a reactive and proactive defense against cyber threats.