FGSM – Red Team AI Labs

30May

FGSM in Convolutional Neural Networks

This post is a continuation of the previous one: “A Practical Introduction to FGSM.”

FGSM Practical Fundamentals

Here, we will focus on a Convolutional Neural Network. Convolutional Neural Networks (CNNs) represent one of the most significant breakthroughs in the field of artificial intelligence.

Their history began in 1998 when Yann LeCun introduced LeNet-5, the first successful CNN, used for handwritten digit recognition.

http://vision.stanford.edu/cs598_spring07/papers/Lecun98.pdf

However, the real turning point came in 2012 with AlexNet, developed by Alex Krizhevsky, which won the ImageNet competition with a staggering lead over traditional methods.

23May

FGSM Practical Fundamentals

by user Adversarial Machine Learning

This will be our first hands-on post, and we’re starting with a very visual type of attack that we can implement for free using services like Google Colab or in local environments with Anaconda/Miniconda, a Python virtual environment, Docker, or any other setup you’re more comfortable with.

Neural networks—specifically convolutional neural networks (CNNs)—are commonly used in computer vision tasks such as image classification, object detection, facial recognition, and more.