1. Machine Learning (ML)
- Supervised learning - Training models on labeled datasets to classify threats
- Unsupervised learning - Detecting anomalies without prior knowledge of threats
- Reinforcement learning - Improving response strategies through trial and feedback
2. Natural Language Processing (NLP)
- Threat intelligence parsing - Extracting actionable insights from unstructured data
- Automated report generation - Creating human-readable incident summaries
- Communication analysis - Detecting social engineering and phishing attempts
3. Computer Vision
- Network topology visualization - Understanding complex network relationships
- Malware analysis - Analyzing code patterns and behaviors
- User behavior monitoring - Detecting suspicious activities through visual patterns