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adaptive-5g-iiot-backdoor-detection

Official implementation of the IEEE TII paper: 'Adaptive Backdoor Trigger Detection in Edge-Deployed DNNs in 5G-Enabled IIoT Systems'

advanced-gradient-obfuscating

Take further steps in the arms race of adversarial examples with only preprocessing.

backdoor-learning-resources

A curated list of backdoor learning resources

backdoorbox

cvpr-latex-template

Extended LaTeX template for CVPR/ICCV papers

decodingtrust

A Comprehensive Assessment of Trustworthiness in GPT Models

deepsweep

An evaluation framework for mitigating DNN backdoor attacks using data augmentations

fencebox

The official FenceBox Platform -- implementation of paper:' FenceBox A Platform for Defeating Adversarial Examples with Data Augmentation Techniques.'

frequency-backdoor

ICCV 2021, We find most existing triggers of backdoor attacks in deep learning contain severe artifacts in the frequency domain. This Repo. explores how we can use these artifacts to develop stronger backdoor defenses and attacks.

i-bau

Official Implementation of ICLR 2022 paper, ``Adversarial Unlearning of Backdoors via Implicit Hypergradient''

meta-sift

The official implementation of Meta-Sift -- Ten minutes or less to find a 1000-size or larger clean subset on any poisoned dataset.

nad

This is an implementation demo of the ICLR 2021 paper [Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks](https://openreview.net/pdf?id=9l0K4OM-oXE) in PyTorch.

narcissus-backdoor-attack

The official implementation of Narcissus clean-label backdoor attack -- only takes THREE images to poison a face recognition dataset in a clean-label way and achieves a 99.89% attack success rate.

persuasive-llm-jailbreak.github.io

requirements

Simple requirements.txt based example

universal_pert_cert

This repo is the official implementation of the ICLR'23 paper "Towards Robustness Certification Against Universal Perturbations." We calculate the certified robustness against universal perturbations (UAP/ Backdoor) given a trained model.

yizeng623.github.io