Differential-Privacy-Guide
adversarial-robustness-toolbox
| Differential-Privacy-Guide | adversarial-robustness-toolbox | |
|---|---|---|
| 1 | 8 | |
| 13 | 4,460 | |
| - | 1.2% | |
| 2.6 | 9.7 | |
| over 2 years ago | 10 days ago | |
| Python | Python | |
| - | MIT License |
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Differential-Privacy-Guide
adversarial-robustness-toolbox
- [D] Couldn't devs of major GPTs have added an invisible but detectable watermark in the models?
- [D] ML Researchers/Engineers in Industry: Why don't companies use open source models more often?
- [D]: How safe is it to just use a strangers Model?
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[D] Does anyone care about adversarial attacks anymore?
Check out this project https://github.com/Trusted-AI/adversarial-robustness-toolbox
- adversarial-robustness-toolbox: Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
- Library for Machine Learning Security Evasion, Poisoning, Extraction, Inference
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Introduction to Adversarial Machine Learning
Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to defend and evaluate Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference.
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[D] Testing a model's robustness to adversarial attacks
Depending on what attacks you want I've found both https://github.com/cleverhans-lab/cleverhans and https://github.com/Trusted-AI/adversarial-robustness-toolbox to be useful.
What are some alternatives?
tf-encrypted - A Framework for Encrypted Machine Learning in TensorFlow
DeepRobust - A pytorch adversarial library for attack and defense methods on images and graphs
gretel-python-client - The Gretel Python Client allows you to interact with the Gretel REST API.
auto-attack - Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"
ReTube - ReImagine Tubing
TextAttack - TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/
privacy - Library for training machine learning models with privacy for training data
alpha-zero-boosted - A "build to learn" Alpha Zero implementation using Gradient Boosted Decision Trees (LightGBM)
isp-data-pollution - ISP Data Pollution to Protect Private Browsing History with Obfuscation
m2cgen - Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
waf-bypass - Check your WAF before an attacker does
gretel-synthetics - Synthetic data generators for structured and unstructured text, featuring differentially private learning.