Day 1: Introduction to Dark Web & AI in Cyber Intelligence
🧠 Topics:
- Surface, Deep & Dark Web: Differences and Myths
- Use of Tor, I2P, and Freenet
- Dark Web Marketplaces, Forums, and Crypto Use
- Introduction to AI/ML in Cybersecurity
- Types of AI used in dark web monitoring (NLP, anomaly detection, image recognition)
🛠️ Tools/Activity:
- Live demo: Tor Browser navigation (safe content)
- Overview of AI pipeline for threat intelligence
- Group discussion: Dark web ethics and legal considerations
Day 2: OSINT & Data Mining from Dark Web
🧠 Topics:
- What is OSINT? Applications in dark web intel
- Web scraping techniques (Python + BeautifulSoup / Scrapy)
- Use of AI for content classification
- Introduction to Maltego, Spiderfoot
🛠️ Tools/Activity:
- Practical: Extracting data from onion sites (using simulation environment)
- Scraping and structuring content
- Lab: Classifying forum posts using pre-trained NLP model (HuggingFace/BERT)
Day 3: AI-Powered Threat Detection and Monitoring
🧠 Topics:
- Sentiment Analysis, Keyword Extraction from forums/chats
- Entity Recognition (products, people, locations)
- AI models for anomaly detection (e.g., drug trade, malware sales)
- Introduction to Dark Web Monitoring Platforms (DarkOwl, DarkSearch, IntSights)
🛠️ Tools/Activity:
- Lab: Use Python to detect malicious intent using sentiment classifier
- Visualize network of actors using Gephi/Maltego
- Demo: Alert generation using keyword + AI classifier
Day 4: Case Study & Mini Project
🧠 Topics:
Real-world cases: Ransomware, Human Trafficking, Fake Passport Networks
Project walkthrough: AI pipeline for real-time dark web alerting
- Ethical AI and bias issues in dark web monitoring
Career paths: Threat Intel Analyst, SOC Analyst, OSINT Investigator
Project/Activity:
- Mini Project: Build a Dark Web Alert System using scraped data + AI model
- Team presentation on case study: Choose one dark web threat area and outline how AI could detect it
