PhD/MSc course on Machine Learning Security (Univ. Cagliari)

A Survey of Poisoning Attacks and Defenses in Recommender Systems

FedAnil+ is a novel lightweight, and secure Federated Deep Learning Model to address non-IID data, privacy concerns, and communication overhead. This repo hosts a simulation for FedAnil+ written in Python.

Test tool to simulate defense from poisoning attack on AI model

This project uses Python and machine learning to classify plant species as poisonous or non-poisonous. It aims to provide an efficient way to identify safe and harmful plants, useful for botanists, hikers, and the agricultural sector.

Test tool to simulate two types of poisoning attack on AI model

Official Website of https://github.com/tamlhp/awesome-recsys-poisoning

M. Anisetti, C. A. Ardagna, A. Balestrucci, N. Bena, E. Damiani, C. Y. Yeun. "On the Robustness of Random Forest Against Data Poisoning: An Ensemble-Based Approach". In IEEE TSUSC, vol. 8 no. 4

FedAnil is a secure blockchain-enabled Federated Deep Learning Model to address non-IID data and privacy concerns. This repo hosts a simulation for FedAnil written in Python.

FedAnil++ is a Privacy-Preserving and Communication-Efficient Federated Deep Learning Model to address non-IID data, privacy concerns, and communication overhead. This repo hosts a simulation for FedAnil++ written in Python.

A Python library for Secure and Explainable Machine Learning

Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)

Taller de Adversarial Machine Learning

Poisoning attack methods against adversarial training algorithms

Continuous Integration And Continuous Delivery Poisoning Guides

The official implementation of the CCS'23 paper, 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.

Hack tool for local network: Man in the middle, hosts scan, ARP poisoning, Router and DNS Poisoning

Paper collection of federated learning. Conferences and Journals Collection for Federated Learning from 2019 to 2021, Accepted Papers, Hot topics and good research groups. Paper summary

Tensorflow implementation of TrialAttack (Triple Adversarial Learning for Influence based Poisoning Attack in Recommender Systems. KDD 2021)