Yellow - AI, Machine Learning, and FOSS

AI Tools

AI Tool Collections

• https://theresanaiforthat.com/alphabetical/

• https://www.futurepedia.io/

• https://www.aishrine.com/

• https://theresanaiforthat.com/

Interesting AI Articles

• https://www.computerweekly.com/news/252529081/Should-we-be-worried-about-malicious-use-of-AI-language-models

• https://apnews.com/article/technology-education-colleges-and-universities-france-a0ab654549de387316404a7be019116b

Prompt Crafting

• https://prmpts.carrd.co/

FOSS - Free and Open Source Software

• https://www.opensourcealternative.to/

Machine Learning

Attack Research

Proper research all starts with one thing: Data!

• DetectionLab - Automate the creation of a lab environment complete with security tooling and logging best practices

• Mitre CAR - The MITRE Cyber Analytics Repository (CAR) is a knowledge base of analytics developed by MITRE based on the MITRE ATT&CK adversary model.

  • CAR is focused on providing a set of validated and well-explained analytics, in particular with regards to their operating theory and rationale.

• soc-faker - A python package for use in generating fake data for SOC and security automation.

Datasets

• Awesome Lists Collection: Security Data Sets

• VizSec research and development data sets

• Splunk Security Dataset - Access real data in Splunk hosted portal and explore/analyze various datasets with an educational tutorial.

• OTRF/Security-Datasets - The Open Threat Research Forge project is an open-source initiatve that contributes malicious and benign datasets, from different platforms, to the infosec community to expedite data analysis and threat research.

• SecRepo - Security Data Samples Repository

• PCAP-ATTACK - PCAP Samples for Different Post Exploitation Techniques

• EVTX-ATTACK-SAMPLES - Windows Events Attack Samples

• Public PCAP files for download - This is a list of public packet capture repositories, which are freely available on the Internet. Most of the sites listed below share Full Packet Capture (FPC) files, but some do unfortunately only have truncated frames.

• Splunk Boss of the SOC version 3 dataset. Datasets from one of the biggest data mining competitions in the world. Perfect for Splunk training or developing search used cases.

• PhishingKitTracker - Samples of phishing kits for use in security research

Network Analysis through Machine Learning

• Awesome Lists Collection: Network Analysis

• Incremental Machine Learning by Example: Detecting Suspicious Activity with Zeek Data Streams, River, and JA3 Hashes – NCC Group Research

• Applying Machine Learning to Network Anomalies | Part 1 - YouTube

• Machine Learning Techniques for Intrusion Detection - machine-learning-techniques-intrusion-detection-40330.pdf

• IT Security From The Eyes Of Data Scientists

• How Enterprises Can Use Big Data To Improve Security

Machine Learning Books

Machine Learning Books

• A Brief Introduction to Machine Learning for Engineers - Osvaldo Simeone (PDF)

• A Brief Introduction to Neural Networks

• A Comprehensive Guide to Machine Learning - Soroush Nasiriany, Garrett Thomas, William Wang, Alex Yang (PDF)

• A Course in Machine Learning (PDF)

• A First Encounter with Machine Learning (PDF)

• A Selective Overview of Deep Learning - Fan, Ma, and Zhong (PDF)

• Algorithms for Reinforcement Learning - Csaba Szepesvári (PDF)

• An Introduction to Statistical Learning - Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani

• Bayesian Reasoning and Machine Learning

• Deep Learning - Ian Goodfellow, Yoshua Bengio and Aaron Courville

• Deep Learning for Coders with Fastai and PyTorch - Jeremy Howard, Sylvain Gugger (Jupyter Notebooks)

• Deep Learning with PyTorch - Eli Stevens, Luca Antiga, Thomas Viehmann (PDF)

• Dive into Deep Learning

• Explorations in Parallel Distributed Processing: A Handbook of Models, Programs, and Exercises - James L. McClelland

• Foundations of Machine Learning, Second Edition - Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar

• Free and Open Machine Learning - Maikel Mardjan

• Gaussian Processes for Machine Learning

• IBM Machine Learning for Dummies - Judith Hurwitz, Daniel Kirsch

• Information Theory, Inference, and Learning Algorithms

• Interpretable Machine Learning - Christoph Molnar

• Introduction to CNTK Succinctly - James McCaffrey

• Introduction to Machine Learning - Amnon Shashua

• Keras Succinctly - James McCaffrey

• Learn Tensorflow - Jupyter Notebooks

• Learning Deep Architectures for AI (PDF)

• Machine Learning

• Machine Learning for Data Streams - Albert Bifet, Ricard Gavaldà, Geoff Holmes, Bernhard Pfahringer

• Machine Learning from Scratch - Danny Friedman

• Machine Learning, Neural and Statistical Classification

• Mathematics for Machine Learning - Garrett Thomas (PDF)

• Mathematics for Machine Learning - Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong

• Neural Networks and Deep Learning

• Probabilistic Models in the Study of Language (Draft, with R code)

• Python Machine Learning Projects - Lisa Tagliaferri and Brian Boucheron (PDF, EPUB, MOBI)

• Reinforcement Learning: An Introduction - Richard S. Sutton, Andrew G. Barto (PDF)

• Speech and Language Processing (3rd Edition Draft) - Daniel Jurafsky, James H. Martin (PDF)

• The Elements of Statistical Learning - Trevor Hastie, Robert Tibshirani, and Jerome Friedman

• The LION Way: Machine Learning plus Intelligent Optimization - Roberto Battiti, Mauro Brunato (PDF)

• The Python Game Book

• Top 10 Machine Learning Algorithms Every Engineer Should Know - Binny Mathews and Omair Aasim

• Understanding Machine Learning: From Theory to Algorithms - Shai Shalev-Shwartz, Shai Ben-David