There are 1 repository under poisoning-attack topic.
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
Example of using ELF hacking to inject malicious code into a target binary
[UbiComp/IMWUT '23] Hierarchical Clustering-based Personalized Federated Learning for Robust and Fair Human Activity Recognition
My experiments in weaponizing ONOS applications (https://github.com/opennetworkinglab/onos)
Code for "Biometric Backdoors: A Poisoning Attack Against Unsupervised Template Updating"
Source code for the Energy-Latency Attacks via Sponge Poisoning paper.
[Preprint] On the Effectiveness of Mitigating Data Poisoning Attacks with Gradient Shaping
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.
FedDefender is a novel defense mechanism designed to safeguard Federated Learning from the poisoning attacks (i.e., backdoor attacks).
An isolated environment for DNS cache poisoning attack investigation and demonstration.
Course Project for EE782. IIT Bombay, Autumn 2019
Perception Poisoning Attacks in Federated Learning
Implementation of the dns cache poisoning attack reloaded (ACM CCS '20) replication.
Implementations on Security and Privacy in ML; Evasion Attack, Model Stealing, Model Poisoning, Membership Inference Attacks, ...
Venom is an ARP-Poisoner that sniffs TLS requests to take advantage of SNI Leak and display all targets DNS traffic even if it is encrypted.
Research work on biometric security and template updation using Machine Learning.
This repository contains the code for our USENIX Security'23 paper "PORE: Provably Robust Recommender Systems against Data Poisoning Attacks"
Paper "An LLM-Assisted Easy-to-Trigger Poisoning Attack on Code Completion Models: Injecting Disguised Vulnerabilities against Strong Detection"
Can Adversarial training defend against Poisoning attacks?
Source code for our paper "Leveraging Diffusion-Based Image Variations for Robust Training on Poisoned Data" (NeurIPS 2023 Workshop).
Official Website of https://github.com/tamlhp/awesome-recsys-poisoning
An isolated environment for DNS cache poisoning attack investigation and demonstration.
Explanation-Guided Backdoor Poisoning Attacks Against Malware Classifiers: Verification and Testing (university project for Cybersecurity)
my first thesis paper's code
Simulation of FL in python for Digit Recognition ML model. Simulated poisoning attacks and studies their impact.
Adversarial-Attacks-and-Defence
dnspoison inyecta respuestas dns con IP host falso