secure-xgboost VS federated-xgboost

Compare secure-xgboost vs federated-xgboost and see what are their differences.

secure-xgboost

Secure collaborative training and inference for XGBoost. (by mc2-project)
Machine Learning collaborative-learning Security Privacy enclave Xgboost Data Science
Source Code
mc2-project.github.io
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federated-xgboost

Federated gradient boosted decision tree learning (by mc2-project)
federated-learning federated-xgboost Machine Learning Security
Source Code
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secure-xgboost federated-xgboost
1 1
101 64
- -
0.0 1.2
over 1 year ago about 1 year ago
C++ C++
Apache License 2.0 -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

secure-xgboost

Posts with mentions or reviews of secure-xgboost. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-06-17.
  • Announcing MC²: Securely perform analytics and machine learning on confidential data
    7 projects | dev.to | 17 Jun 2021
    The MC2 Compute Services: MC2 offers several compute services: these include Spark SQL, distributed XGBoost, and secure aggregation for federated learning. All are intended to run in a primarily untrusted environment, such as a cluster of machines hosted on a public cloud, that has support for trusted execution environments (hardware enclaves). Data is encrypted in transit using a client key and only ever decrypted inside hardware enclaves, providing the previously mentioned security guarantees for data-in-use. For all compute services, MC2 leverages the Open Enclave SDK, a project intended to provide a consistent API for a variety of different enclave architectures.

federated-xgboost

Posts with mentions or reviews of federated-xgboost. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-22.

What are some alternatives?

When comparing secure-xgboost and federated-xgboost you can also consider the following projects:

delphi - A Cryptographic Inference Service for Neural Networks

flower - Flower: A Friendly Federated Learning Framework

mc2 - A Platform for Secure Analytics and Machine Learning

FedML - FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, FEDML Nexus AI (https://fedml.ai) is your generative AI platform at scale.

cerebro - Cerebro: A platform for Secure Coopetitive Learning

opaque-sql - An encrypted data analytics platform

breaching - Breaching privacy in federated learning scenarios for vision and text

twinning - Data Twinning

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

secure-aggregation - Secure aggregation for federated learning using enclaves

keepassxc - KeePassXC is a cross-platform community-driven port of the Windows application “Keepass Password Safe”.

secure-xgboost vs delphi federated-xgboost vs flower secure-xgboost vs mc2 federated-xgboost vs FedML secure-xgboost vs cerebro federated-xgboost vs mc2 secure-xgboost vs opaque-sql federated-xgboost vs breaching secure-xgboost vs twinning federated-xgboost vs AIJack secure-xgboost vs secure-aggregation federated-xgboost vs keepassxc