Adversarial Machine Learning » THOVITI SIDDHARTH

May 27, 2024

Part 3 – Projected Gradient Descent (PGD)

Thoviti Siddharth Machine Learning/Artificial Intelligence Adversarial Machine Learning, Fast Gradient Sign Method, FGSM, Machine Learning Hacking, PGD, PGD Attack, Projected Gradient Descent, PyTorch, ResNet50 0

Welcome to Part 3 of our blog series on Adversarial Machine Learning! In this installment, we will delve into the intricacies of the Projected Gradient Descent (PGD) method—a powerful iterative technique for crafting adversarial examples. We will explore how PGD enhances the Fast Gradient Sign Method (FGSM) by iterating and refining the perturbations, leading to more robust and effective attacks. I will also provide a step-by-step code implementation of PGD using PyTorch and compare the attack success rates of FGSM and PGD.

June 19, 2023

Part 2 – Fast Gradient Sign Method (FGSM)

Thoviti Siddharth Machine Learning/Artificial Intelligence Adversarial Attack, Adversarial Machine Learning, Fast Gradient Sign Method, FGSM, Fine-Tuning, PyTorch, ResNet50 0

Welcome to Part 2 of our blog series on Adversarial Machine Learning! In this installment, we will explore the Fast Gradient Sign Method (FGSM), one of the most widely used and effective adversarial attack techniques. We will understand how the attack works, its significance, and implement the attack through PyTorch code.

June 14, 2023

Part 1 – Introduction to Adversarial Machine Learning

Thoviti Siddharth Machine Learning/Artificial Intelligence Adversarial Example, Adversarial Machine Learning, Distance Metrics 0

Welcome to the first part of our blog series on Adversarial Machine Learning! In this series, we will explore the fascinating field of adversarial machine learning, its background, techniques for attacks, and strategies for defense. Let’s begin with an introduction to adversarial machine learning and its relevance in today’s landscape.