对抗样本（Adversarial Examples）和投毒攻击（Poisoning Attacks）相关资料

Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective".

A repository to quickly generate synthetic data and associated trojaned deep learning models

Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective".

A Survey of Poisoning Attacks and Defenses in Recommender Systems

[UbiComp/IMWUT '23] Hierarchical Clustering-based Personalized Federated Learning for Robust and Fair Human Activity Recognition

Example of using ELF hacking to inject malicious code into a target binary

Source code for the Energy-Latency Attacks via Sponge Poisoning paper.

My experiments in weaponizing ONOS applications (https://github.com/opennetworkinglab/onos)

Code for "Biometric Backdoors: A Poisoning Attack Against Unsupervised Template Updating"

FedDefender is a novel defense mechanism designed to safeguard Federated Learning from the poisoning attacks (i.e., backdoor attacks).

A Semi-supervised learning model (Ladder Network) to classify MNIST digits. A few attacks were executed on it with the target of misclassifying 4s with 9s.

[Preprint] On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping

An isolated environment for DNS cache poisoning attack investigation and demonstration.

The code for ACM MM2024 (Multimodal Unlearnable Examples: Protecting Data against Multimodal Contrastive Learning)

Course Project for EE782. IIT Bombay, Autumn 2019

USENIX Security'24 Paper Repo

This repository contains the code for our USENIX Security'23 paper "PORE: Provably Robust Recommender Systems against Data Poisoning Attacks"

Implementations on Security and Privacy in ML; Evasion Attack, Model Stealing, Model Poisoning, Membership Inference Attacks, ...