[D] Testing a model's robustness to adversarial attacks

• adversarial-robustness-toolbox

  8 4,460 9.7 Python

  Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

  

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.

• auto-attack

  3 607 0.0 Python

  Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"

A better method is to use the AutoAttack from Croce et al. https://github.com/fra31/auto-attack which is much more robust to gradient masking. It's actually a combination of 3 attacks (2 white-box and 1 black box) with good default hyper-parameters. It's not perfect but it gives a more accurate robustness.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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