Whitebox-adversarial-toolbox

Latest version: v0.2.0

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0.1.0

<img src="https://what.wuhanstudio.uk/images/what.png" width=300px style="float: left;" >

WHite-box Adversarial Toolbox (WHAT)

A Python Library for Deep Learning Security that focuses on Real-time White-box Attacks.

![](docs/images/demo.gif)

Installation

python
pip install whitebox-adversarial-toolbox


Usage (CLI)


Usage: what [OPTIONS] COMMAND [ARGS]...

The CLI tool for WHitebox-box Adversarial Toolbox (what).

Options:
--help Show this message and exit.

Commands:
attack Manage Attacks
example Manage Examples
model Manage Deep Learning Models


Useful commands:


List supported models
$ what model list

List supported Attacks
$ what attack list

List available examples
$ what example list


Supported Models


[x] 1 : YOLOv3 ( Darknet ) Object Detection YOLOv3 pretrained on MS COCO dataset.
[x] 2 : YOLOv3 ( Mobilenet ) Object Detection YOLOv3 pretrained on MS COCO dataset.
[x] 3 : YOLOv3 Tiny ( Darknet ) Object Detection YOLOv3 Tiny pretrained on MS COCO dataset.
[x] 4 : YOLOv3 Tiny ( MobileNet ) Object Detection YOLOv3 Tiny pretrained on MS COCO dataset.
[x] 5 : YOLOv4 ( Darknet ) Object Detection YOLOv4 pretrained on MS COCO dataset.
[x] 6 : YOLOv4 Tiny ( Darknet ) Object Detection YOLOv4 Tiny pretrained on MS COCO dataset.
[x] 7 : SSD ( MobileNet v1 ) Object Detection SSD pretrained on VOC-2012 dataset.
[x] 8 : SSD ( MobileNet v2 ) Object Detection SSD pretrained on VOC-2012 dataset.
[x] 9 : FasterRCNN ( VGG16 ) Object Detection Faster-RCNN pretrained on VOC-2012 dataset.


Supported Attacks

Use `what attack list` to list available attacks:


1 : TOG Attack Object Detection
2 : PCB Attack Object Detection


- [A Man-in-the-Middle Attack against Object Detection Systems](https://arxiv.org/abs/2208.07174).
- [Adversarial Objectness Gradient Attacks in Real-time Object Detection Systems](https://ieeexplore.ieee.org/document/9325397).

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Available Examples


Demo Type Description
--------------------------------------------------------------------------------
1 : Yolov3 Demo Model Inference Yolov3 Object Detection.
2 : Yolov4 Demo Model Inference Yolov4 Object Detection.
3 : FasterRCNN Demo Model Inference FRCNN Object Detection.
4 : MobileNet SSD Demo Model Inference MobileNet SSD Object Detection.
5 : TOG Attack Demo Adversarial Attack Real-time TOG Attack against Yolov3 Tiny.
6 : PCB Attack Demo Adversarial Attack Real-time PCB Attack against Yolov3 Tiny.

Links

Releases

Has known vulnerabilities

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