Adversarial Attacks on Image Classification Models: FGSM and Patch Attacks and their Impact

Understand

This chapter introduces the concept of adversarial attacks on image classification models built on convolutional neural networks (CNN).

• CNNs are very popular deep-learning models which are used in image classification tasks.
• However, very powerful and pre-trained CNN models working very accurately on image datasets for image classification tasks may perform disastrously when the networks are under adversarial attacks.
• In this work, two very well-known adversarial attacks are discussed and their impact on the performance of image classifiers is analyzed.