Cracking Random Number Generators using Machine Learning – Part 2: Mersenne Twister
Outline 1. Introduction 2. How does MT19937 PRNG work? 3. Using Neural Networks to model the MT19937 PRNG 3.1 Using NN for State Twisting 3.1.1 Data Preparation 3.1.2 Neural Network Model Design 3.1.3 Optimizing the NN Inputs 3.1.4 Model Results 3.1.5 Model Deep Dive 3.1.5.1 Model First Layer Connections 3.1.5.2 The Logic Closed-Form from the State […]
Cracking Random Number Generators using Machine Learning – Part 1: xorshift128
Outline 1. Introduction 2. How does xorshift128 PRNG work? 3. Neural Networks and XOR gates 4. Using Neural Networks to model the xorshift128 PRNG 4.1 Neural Network Model Design 4.2 Model Results 4.3 Model Deep Dive 5. Creating a machine-learning-resistant version of xorshift128 6. Conclusion 1. Introduction This blog post proposes an approach to crack Pseudo-Random […]