FuzzCoAP - Fuzzing for Robustness and Security Testing of CoAP Servers
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Updated
Jun 23, 2018 - Python
FuzzCoAP - Fuzzing for Robustness and Security Testing of CoAP Servers
NIPS Adversarial Vision Challenge
Code, documents, and deployment configuration files, related to our participation in the 2018 NIPS Adversarial Vision Challenge "Robust Model Track"
Desktop, Mobile and command line smart password deterministic generator
Evaluate robustness of image processing algorithms
A simple library for adding noise to data.
Official TensorFlow Implementation of Adversarial Training for Free! which trains robust models at no extra cost compared to natural training.
[ICCV'19] Improving Adversarial Robustness via Guided Complement Entropy
A implementation of Power Normalized Cepstral Coefficients: PNCC
A method for training neural networks that are provably robust to adversarial attacks. [IJCAI 2019]
[NAACL 2018] Robust Sequence Labeling with Adversarial Training
Code for ICCV2019 paper《Adversarial Learning with Margin-based Triplet Embedding Regularization》
TF2.0 port for Augmix paper
Fastened CROWN: Tightened Neural Network Robustness Certificates
Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"
OOD Generalization and Detection (ACL 2020)
An Algorithm to Quantify Robustness of Recurrent Neural Networks
Code for ICML2019 Paper "On the Convergence and Robustness of Adversarial Training"
Python Script that can investigate the robustness of a network by simulating failures and target attacks
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