对抗样本(Adversarial Examples)和投毒攻击(Poisoning Attacks)相关资料
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Updated
Jun 3, 2019
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)
Source code for the Energy-Latency Attacks via Sponge Poisoning paper.
Code for "Biometric Backdoors: A Poisoning Attack Against Unsupervised Template Updating"
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.
FedDefender is a novel defense mechanism designed to safeguard Federated Learning from the poisoning attacks (i.e., backdoor attacks).
Course Project for EE782. IIT Bombay, Autumn 2019
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.
Implementation of the dns cache poisoning attack reloaded (ACM CCS '20) replication.
Perception Poisoning Attacks in Federated Learning
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