ml_for_infosec.md

Machine Learning applications in information security

Keeping record of all resources that were shared in the ml-for-infosec channel of 42 AI Slack workspace by grouping them in this repository.

42 Artificial Intelligence is a student organization of the Paris campus of the school 42. Its purpose is to foster discussion, learning, and interest in the field of artificial intelligence, by organizing various activities such as lectures and workshops.

📺 Videos

• Introduction to AI & Machine Learning - w/InsiderPhD
• DEF CON 27 AI Village playlist
• Offensive and defensive security with machine learning (J. I. Escribano) T1 - CyberCamp 2017 (EN)
• 🇫🇷 SSTIC 2017: Le Machine Learning confronté aux contraintes opérationnelles des systèmes de détection
• "AI & Machine Learning" Cybersecurity Conversation

📃 Articles

• Machine Learning for Cybersecurity 101
• Malware Analysis with Visual Pattern Recognition
• Machine learning – Predict vulnerabilities by examining the words in a URL
• DARPA Cyber Grand Challenge (CGC) (Archived)
• Dangerous Pickles — Malicious Python Serialization

SOC / SIEM

• Developments in Machine Learning vs. Traditional SIEM Solutions
• Using Machine Learning and Analytics to Hunt for Security Threats
• The state of machine learning and the SOC: How to leverage the data deluge
• 🇫🇷 MISC n°110 (paper magazine), Prise en main du machine learning avec Splunk

OSINT

• What is OSINT? How can I make use of it?
• OSINTCurio.us: Python, Your Friendly OSINT Helper
• OSINTCurio.us: Data Scraping and Visualizing using Instant Data Scraper, ViewDNS.info, and Maltego
• conINT 2020 - Intelligence Conference & CTF
• Automating OSINT

Adversarial Machine Learning

• AI Security and Adversarial Machine Learning 101
• Microsoft launches machine learning cyber-attack threat matrix
• adversarial.js

Using GPUs for training your ML models

• Using GPUs for training models in the cloud
• Building your own deep learning box
• The NVIDIA Deep Learning Institute

📚 Books

• Machine Learning and Security by Clarence Chio and David Freeman, 2018
• Mastering Machine Learning for Penetration Testing by Chiheb Chebbi

🔬 Studies

• Detecting Anomalous User Behavior Using an Extended Isolation Forest Algorithm: An Enterprise Case Study
• Anomaly detection; Industrial control systems; convolutional neural networks

📊 Kaggle datasets

• Microsoft Malware Classification Challenge
• Microsoft Malware Prediction

👓 Repositories

• Awesome Machine Learning for Cyber Security

Use cases

• ROXANNE

Acknowledgements

Merci à toutes les personnes qui contribuent et animent le canal ! 🤖💙