Advbox Family is a series of AI model security tools set of Baidu Open Source,including the generation, detection and protection of adversarial examples, as well as attack and defense cases for different AI applications.
- Tracking the Criminal of Fake News Based on a Unified Embedding. Blackhat Asia 2020
- Attacking and Defending Machine Learning Applications of Public Cloud. Blackhat Asia 2020
- ABSTRACT:Cloud-based Image Classification Service Is Not Robust To Affine Transformation : A Forgotten Battlefield. CCSW 2019: The ACM Cloud Computing Security Workshop of CCS 2019
- TRANSFERABILITY OF ADVERSARIAL EXAMPLES TO ATTACK REAL WORLD PORN IMAGES DETECTION SERVICE.HITB CyberWeek 2019
- COMMSEC: Tracking Fake News Based On Deep Learning. HITB GSEC 2019
- COMMSEC: Hacking Object Detectors Is Just Like Training Neural Networks. HITB GSEC 2019 | See code
- COMMSEC: How to Detect Fake Faces (Manipulated Images) Using CNNs. HITB GSEC 2019
- Transferability of Adversarial Examples to Attack Cloud-based Image Classifier Service. Defcon China 2019
- Face Swapping Video Detection with CNN. Defcon China 2019
A Lightweight Adv SDK For PaddlePaddle to generate adversarial examples.
Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models.Advbox give a command line tool to generate adversarial examples with Zero-Coding.
AdvDetect is a toolbox to detect adversarial examples from massive data.
Data poisoning
Homepage of Face Recogniztion Attack
On defcon, we demonstrated T-shirts that can disappear under smart cameras. Under this sub-project, we open-source the programs and deployment methods of smart cameras for demonstration.
The restful API is used to detect whether the face in the picture/video is a false face.
If you instead use AdvBox in an academic publication, cite as:
@misc{goodman2020advbox,
title={Advbox: a toolbox to generate adversarial examples that fool neural networks},
author={Dou Goodman and Hao Xin and Wang Yang and Wu Yuesheng and Xiong Junfeng and Zhang Huan},
year={2020},
eprint={2001.05574},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
Cloud-based Image Classification Service is Not Robust to Affine Transformation: A Forgotten Battlefield
@inproceedings{goodman2019cloud,
title={Cloud-based Image Classification Service is Not Robust to Affine Transformation: A Forgotten Battlefield},
author={Goodman, Dou and Hao, Xin and Wang, Yang and Tang, Jiawei and Jia, Yunhan and Wei, Tao and others},
booktitle={Proceedings of the 2019 ACM SIGSAC Conference on Cloud Computing Security Workshop},
pages={43--43},
year={2019},
organization={ACM}
}
- Pablo Navarrete Michelini, Hanwen Liu, Yunhua Lu, Xingqun Jiang; A Tour of Convolutional Networks Guided by Linear Interpreters; The IEEE International Conference on Computer Vision (ICCV), 2019, pp. 4753-4762
- Ling, Xiang and Ji, Shouling and Zou, Jiaxu and Wang, Jiannan and Wu, Chunming and Li, Bo and Wang, Ting; Deepsec: A uniform platform for security analysis of deep learning model ; IEEE S&P, 2019
- Deng, Ting and Zeng, Zhigang; Generate adversarial examples by spatially perturbing on the meaningful area; Pattern Recognition Letters[J], 2019, pp. 632-638
https://github.com/baidu/AdvBox/issues
AdvBox support Apache License 2.0