Adversarial Learning

Testing the robustness of your models by using adversarial attacks.


Introduction to Adversarial Machine Learning
In this article we are going to learn about a handful of attacks, namely how they work and how we can defend networks against these attacks.
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How to Steal Modern NLP Systems with Gibberish?
It’s possible to steal BERT-based models without any real training data, even using gibberish word sequences.
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Adversarial Training Improves Product Discovery
Method automatically generates meaningful negative training examples for deep-learning model.
adversarial-learning adversarial-training product-discovery article
Weight Poisoning Attacks on Pre-trained Models
How Bert can be infused with nefarious behavior, even after fine-tuning.
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Learning Perturbation Sets for Robust Machine Learning
Using generative modeling to capture real-world transformations from data for adversarial robustness.
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NLP Libraries
A Python framework for building adversarial attacks on NLP models.
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CV Libraries
A pytorch adversarial library for attack and defense methods on images and graphs.
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Other Libraries
An adversarial example library for constructing attacks, building defenses, and benchmarking both.
adversarial-learning cleverhans adversarial-attacks article
Advbox Family
Advbox Family is a series of AI model security tools set of Baidu Open Source,including the generation, detection and protection of adversarial examples.
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Foolbox Native
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
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