{"repo":"Koukyosyumei/AIJack","free":true,"listed":false,"github":"https://github.com/Koukyosyumei/AIJack","clone":"git clone https://github.com/Koukyosyumei/AIJack.git","description":"Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)","language":"C++","stars":431,"topics":["security","machine-learning","adversarial-attacks","adversarial-examples","adversarial-machine-learning","membership-inference","model-inversion-attacks","evasion-attack","poisoning-attacks","privacy"],"license":"Apache-2.0","category":"machine-learning","readme_excerpt":"AIJack: Security and Privacy Risk Simulator for Machine Learning What is AIJack? AIJack is an easy-to-use open-source simulation tool for testing the security of your AI system against hijackers. It provides advanced security techniques like Differential Privacy , Homomorphic Encryption , K-anonymity and Federated Learning to guarantee protection for your AI. With AIJack, you can test and simulate defenses against various attacks such as Poisoning , Model Inversion , Backdoor , and Free-Rider . We support more than 30 state-of-the-art methods. For more information, check our paper and documentation and start securing your AI today with AIJack. Installation You can install AIJack with pip . AIJack requires Boost and pybind11. If you want to use the latest-version, you can directly install from GitHub. We also provide Dockerfile. Quick Start We briefly introduce the overview of AIJack. Features - All-around abilities for both attack & defense - PyTorch-friendly design - Compatible with scikit-learn - Fast Implementation with C++ backend - MPI-Backend for Federated Learning - Extensible modular APIs Basic Interface Python API For standard machine learning algorithms, AIJack allows you to simulate attacks against machine learning models with Attacker APIs. AIJack mainly supports PyTorch or sklearn models. For instance, we can implement Poisoning Attack against SVM implemented with sklearn as follows. For distributed learning such as Federated Learning and Split Learning, AIJack o","default_branch":null,"files":null,"tree":[],"storefront":"/r/Koukyosyumei","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Koukyosyumei/AIJack/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}