Cyber Threat Intelligence Framework

Project Overview

This research project developed an innovative framework for automated cyber threat intelligence using advanced machine learning techniques. The system analyzes large-scale text data from hacker forums, dark web sources, and security reports to identify emerging threats and provide actionable intelligence.

Key Contributions

• Large-scale Text Analytics: Implemented novel NLP techniques for processing and analyzing hacker forum content
• Threat Classification: Developed machine learning models for automated threat categorization
• Real-time Monitoring: Created systems for continuous threat assessment and alerting
• Validation Framework: Established methodologies for evaluating threat intelligence accuracy

Research Impact

• Published in top-tier cybersecurity conferences
• Integrated into multiple security operations centers
• Cited by industry practitioners and researchers
• Led to follow-up research in adversarial machine learning

Technologies Used

• Python, TensorFlow, PyTorch
• Natural Language Processing (NLP)
• Deep Learning and Neural Networks
• Big Data Processing (Spark, Hadoop)
• Cybersecurity Tools and Frameworks