spring-epfl / tricksterLinks
Library and experiments for attacking machine learning in discrete domains
☆47Updated 3 years ago
Alternatives and similar repositories for trickster
Users that are interested in trickster are comparing it to the libraries listed below
Sorting:
- Plausible looking adversarial examples for text classification☆94Updated 7 years ago
- Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks [NeurIPS 2019]☆50Updated 5 years ago
- Code for the paper "Weight Poisoning Attacks on Pre-trained Models" (ACL 2020)☆143Updated 4 months ago
- CodeBase for Paper: "Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers", / Interactive Demo @☆80Updated 2 years ago
- A community-run reference for state-of-the-art adversarial example defenses.☆51Updated last year
- ☆37Updated 5 years ago
- Interfaces for defining Robust ML models and precisely specifying the threat models under which they claim to be secure.☆62Updated 6 years ago
- Concealed Data Poisoning Attacks on NLP Models☆21Updated 2 years ago
- Code for "Testing Robustness Against Unforeseen Adversaries"☆80Updated last year
- VizSec17: Web-based visualization tool for adversarial machine learning / LiveDemo☆130Updated 2 years ago
- Implementation code for the paper "Generating Natural Language Adversarial Examples"☆170Updated 6 years ago
- ☆130Updated 4 years ago
- to add☆20Updated 6 years ago
- Implementation of membership inference and model inversion attacks, extracting training data information from an ML model. Benchmarking …☆103Updated 6 years ago
- Benchmarking and Visualization Tool for Adversarial Machine Learning☆189Updated 2 years ago
- A certifiable defense against adversarial examples by training neural networks to be provably robust☆222Updated last year
- Task-agnostic universal black-box attacks on computer vision neural network via procedural noise (CCS'19)☆56Updated 5 years ago
- Detecting Adversarial Examples in Deep Neural Networks☆69Updated 7 years ago
- Circumventing the defense in "Ensemble Adversarial Training: Attacks and Defenses"☆38Updated 7 years ago
- Interval attacks (adversarial ML)☆21Updated 6 years ago
- LaTeX source for the paper "On Evaluating Adversarial Robustness"☆259Updated 4 years ago
- Athena: A Framework for Defending Machine Learning Systems Against Adversarial Attacks☆44Updated 4 years ago
- A concise primer on Differential Privacy☆29Updated 5 years ago
- Code corresponding to the paper "Adversarial Examples are not Easily Detected..."☆90Updated 8 years ago
- ☆33Updated 8 years ago
- Generating Natural Adversarial Examples, ICLR 2018☆142Updated 7 years ago
- A curated list of awesome resources for adversarial examples in deep learning☆265Updated 4 years ago
- EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples☆39Updated 7 years ago
- Generate adversarial text via gradient methods☆30Updated 6 years ago
- To Trust Or Not To Trust A Classifier. A measure of uncertainty for any trained (possibly black-box) classifier which is more effective t…☆177Updated 2 years ago