Community Resources

Learning Paths

🎯 Beginner Track (2-4 weeks)

1. Introduction
2. What are Deepfakes?
3. Detection Basics
4. Prevention Basics

🚀 Intermediate Track (4-8 weeks)

1. Complete Beginner Track
2. Prompt Injection
3. Advanced Detection
4. Incident Response

🔬 Advanced Track (8-12 weeks)

1. Complete Intermediate Track
2. Forensic Analysis
3. Legal Framework
4. Industry Standards
5. Threat Intelligence

Hands-On Labs

Lab 1: Deepfake Detection

git clone https://github.com/durellwilson/ml-text-kit
cd ml-text-kit
python detect.py --input sample.mp4

Lab 2: Prompt Injection Testing

git clone https://github.com/durellwilson/security-framework
cd security-framework
swift test

Research Resources

Academic

• IEEE Xplore: https://ieeexplore.ieee.org/
• ACM Digital Library: https://dl.acm.org/
• arXiv: https://arxiv.org/list/cs.CR/recent

Government

• NIST AI: https://www.nist.gov/topics/artificial-intelligence
• CISA: https://www.cisa.gov/ai
• NSA Guidance: https://www.nsa.gov/

Industry

• OWASP LLM Top 10: https://owasp.org/www-project-top-10-for-large-language-model-applications/
• MITRE ATLAS: https://atlas.mitre.org/
• C2PA: https://c2pa.org/

Contributing

Ways to Contribute

1. Research: Add peer-reviewed findings
2. Code: Improve detection examples
3. Documentation: Clarify explanations
4. Case Studies: Share incidents

See CONTRIBUTING.md

Recognition

• 🌱 Contributor: 1+ merged PR
• 🌿 Regular: 5+ merged PRs
• 🌳 Core: 20+ merged PRs

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