Targeted-Adversarial-Attacks

Getting Started

Prerequisites

• Python 3 (Tested on 3.6.8)
• numpy (Tested on 1.19.3)
• opencv-python (Tested on 4.2.0)
• matplotlib (Tested on 3.0.3)
• TensorFlow 2 (Tested on 2.2.0)

Installation

pip install -r requirements.txt

Usage

python generate_adversarial_example_targeted.py <input_file_name> <target_class_name>

For example:

python generate_adversarial_example_targeted.py input.jpg airliner

In this code sample, ResNet50 model pre-trained on ImageNet is used. You may refer to imagenet_index.json file for a mapping of ImageNet 1000 class labels to their corresponding index.

Authors

• Aaron Chong - Initial work - aaronchong888

See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License - see the LICENSE file for details

Acknowledgments

This project is built referencing the tutorial at pyimagesearch - Targeted adversarial attacks with Keras and TensorFlow, and using the following packages and libraries as listed here