Intelligent Cloud Threat Prediction Engine

Word Count : 4500

Objectives to cover: 

  • Introduction: Overview of AI-powered predictive cloud threat detection.

  • Background: Need for proactive defense against evolving cloud attacks.

  • Problem Statement: Traditional reactive security fails against dynamic cyber threats.

  • Objectives: Forecast threats, reduce breaches, and enhance response speed.

  • Proposed System Architecture: ML engine + threat intelligence + anomaly analysis modules.

  • Data Collection & Preprocessing: Aggregating multi-cloud logs and sanitizing inputs.

  • Machine Learning Techniques: Deep learning & probabilistic models for threat prediction.

  • Evaluation Metrics: Accuracy, false-positive rate, detection latency benchmarks.

  • Conclusion: Ensures proactive, intelligent, and scalable cloud security defense

Reference: APA