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https://github.com/mc2-project/mc2

A Platform for Secure Analytics and Machine Learning
https://github.com/mc2-project/mc2

analytics cloud machine-learning privacy secure-analytics secure-learning security

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A Platform for Secure Analytics and Machine Learning

Host: GitHub
URL: https://github.com/mc2-project/mc2
Owner: mc2-project
License: apache-2.0
Created: 2019-09-11T00:09:56.000Z (about 5 years ago)
Default Branch: dev
Last Pushed: 2023-03-29T01:33:34.000Z (over 1 year ago)
Last Synced: 2024-08-03T01:24:07.037Z (3 months ago)
Topics: analytics, cloud, machine-learning, privacy, secure-analytics, secure-learning, security
Language: C++
Homepage:
Size: 80.2 MB
Stars: 296
Watchers: 20
Forks: 42
Open Issues: 19
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md

Awesome Lists containing this project

Awesome-SGX-Open-Source - https://github.com/mc2-project/mc2

README

# A Platform for Secure Analytics and Machine Learning

![build](https://github.com/mc2-project/mc2/actions/workflows/main.yml/badge.svg)
![docs](https://github.com/mc2-project/mc2/actions/workflows/docs.yml/badge.svg)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[](https://join.slack.com/t/mc2-project/shared_invite/zt-rt3kxyy8-GS4KA0A351Ysv~GKwy8NEQ)
[![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-2.0-4baaaa.svg)](CODE_OF_CONDUCT.md)

![MC2 Overview](client-docs/img/mc2_workflow.jpeg)

Born out of research in the [UC Berkeley RISE Lab](https://rise.cs.berkeley.edu/), [MC²](https://mc2-project.github.io/) is a platform for running secure analytics and machine learning on encrypted data.
With MC², users can outsource their confidential data workloads to the cloud, while ensuring that the data is never exposed unencrypted to the cloud provider.
MC² also enables secure collaboration -- multiple data owners can use the platform to jointly analyze their collective data, without revealing their individual data to each other.

MC² provides the following secure computation services:
* [Opaque SQL](https://github.com/mc2-project/opaque-sql): Encrypted data analytics on Spark SQL using hardware enclaves
* [Secure XGBoost](https://github.com/mc2-project/secure-xgboost): Collaborative XGBoost training and inference on encrypted data using hardware enclaves

The MC² project also includes exploratory research prototypes that develop new cryptographic techniques for secure computation. Please visit the individual project pages for more information:
* [Cerebro](https://github.com/mc2-project/cerebro): A general purpose Python DSL for learning with secure multiparty computation.
* [Delphi](https://github.com/mc2-project/delphi): Secure inference for deep neural networks.
* [Muse](https://github.com/mc2-project/muse): Secure inference resilient to malicious clients.
* [Federated XGBoost](https://github.com/mc2-project/federated-xgboost): Collaborative XGBoost in the federated setting

For more information on MC², visit our [website](https://mc2-project.github.io/).

This repository contains the source code for the **MC² client**, which enables users to easily interface with MC² services deployed remotely in the cloud. **Currently, the client supports remote deployments of Opaque SQL only.** Support for Secure XGBoost is coming soon.
To run an end-to-end MC² workflow:
1. Launch Opaque SQL in the cloud (instructions to do so can be found in the respective repositories)
2. Use the MC² client to encrypt data locally, transfer it to the cloud VMs, run scripts specifying the desired computation, and retrieve and view encrypted results.

## Table of Contents
* [Installation](#installation)
* [Quickstart](#quickstart)
* [Documentation](#documentation)
* [Contact](#contact)

## Installation
To quickly play with MC² Client and Opaque SQL, you can use the provided Dockerfile to build a container (takes ~7 min) with all MC² Client and Opaque SQL dependencies. Alternatively, you can pull a pre-built Docker image instead of building one. To do either, you must have [Docker](https://docs.docker.com/get-docker/) installed.

The container will have the contents of this `mc2` directory at `/mc2/client`, and Opaque SQL will be at `/mc2/opaque-sql`

For ease of use, we recommend that you create a directory within your host `mc2` directory that will serve as your playground, and then mount your `playground` directory to the Docker container. Mounting will ensure that changes you make in your `playground` directory outside the container will be reflected inside the container, and vice versa. If you're bringing your own data, you can either copy your data over to your playground directory, or separately mount your data directory to the container.

### Installation via building an image
```sh
# Clone the `mc2-project/mc2 repo`
git clone https://github.com/mc2-project/mc2.git

# Build a Docker image called `mc2_img`
docker build -t mc2_img .

# Run the container, mounting your playground to the container, and open a shell into the container
docker run -it -v :/mc2/client/playground mc2_img /bin/bash
```

### Installation via pulling an image
If you prefer to pull the image instead, you can pull a pre-built image (~3 GB) from [Docker Hub](https://hub.docker.com/r/mc2project/mc2_img).

```
# Clone the `mc2-project/mc2 repo`
git clone https://github.com/mc2-project/mc2.git

# Pull the mc2_img from Docker Hub
docker pull mc2project/mc2_img:v0.1.3

# Run the container, mounting your playground to the container, and open a shell into the container
docker run -it -v :/mc2/client/playground mc2_img /bin/bash
```

### Installation via build from source
Alternatively, if you'd like to install MC² Client directly on your host, follow [these instructions](https://mc2-project.github.io/client-docs/install.html).

## Quickstart
This quickstart will give you a flavor of using MC² with Opaque SQL, and can be entirely done locally with Docker if desired. You will use MC² Client to encrypt some data, transfer the encrypted data to a remote machine, run an Opaque SQL job on the encrypted data on the remote machine, and retrieve and decrypt the job's encrypted results. To run everything securely, you can choose to spin up Opaque SQL on Azure VMs with SGX-support. Alternatively, to get a flavor of MC² without having to use Azure, you can use the deployment of Opaque SQL in the Docker container.

MC² Client provides a command line interface that enables you to remotely interact with MC² compute services. The CLI relies on a configuration file that you should modify before each step in this quickstart to tell MC² Client what exactly you want to do. An example of the configuration file is [here](demo/config.yaml).

The dataset we'll be using in this quickstart is a medical dataset containing patient records. Here's a couple of sample records for reference.

```sh
Age,BMI,Glucose,Insulin,HOMA,Leptin,Adiponectin,Resistin,MCP.1,Classification
48,23.5,70,2.707,0.467408667,8.8071,9.7024,7.99585,417.114,1
83,20.69049454,92,3.115,0.706897333,8.8438,5.429285,4.06405,468.786,1
82,23.12467037,91,4.498,1.009651067,17.9393,22.43204,9.27715,554.697,1
```

If you get stuck at any point while running the quickstart, feel free to ping us on [Slack](https://join.slack.com/t/mc2-project/shared_invite/zt-rt3kxyy8-GS4KA0A351Ysv~GKwy8NEQ).

### Docker Quickstart
If you'd like to try everything out locally, you can do so within the Docker container you built in the [installation](#installation) section.

1. In the container, copy the contents of the `quickstart` directory to your mounted `playground` directory to ensure that your changes inside the container get reflected on your host. Then, configure MC² Client with your configuration file.

```sh
# From the /mc2/client directory
cp -r quickstart/* playground
mc2 configure $(pwd)/playground/config.yaml
```

1. Generate a keypair and a symmetric key that MC² Client will use to encrypt your data. Specify your username and output paths in the `user` section of the configuration file. Then, generate the keys.

```sh
mc2 init
```

1. Start [Opaque SQL](https://mc2-project.github.io/opaque-sql-docs/src/index.html), a MC² service for secure SQL analytics.

```sh
mc2 start
```

1. Prepare your data for computation by encrypting and uploading it. This step uses the keys you generated in step 2 to encrypt your data. Note that "uploading" here means copying because we have a local deployment.

```sh
mc2 upload
```

1. Run the provided Opaque SQL quickstart script, to be executed by MC². The script can be found [here](quickstart/opaque_sql_demo.scala), and performs a filter operation over our data -- the results will contain records of all patients who are younger than 30 years old. Results are encrypted by MC² before being saved, and can only be decrypted with the key you used to encrypt your data in the previous step.

```sh
mc2 run
```

1. Once computation has finished, you can retrieve your encrypted results and decrypt them. Results are saved in the `results/` directory. You can view the results by looking at `results/opaque_sql_result.dec`

```sh
mc2 download
```

### Azure Quickstart
You can also choose to run this quickstart with enclave-enabled VMs on the cloud with Azure Confidential Computing. Unlike the Docker quickstart, in this quickstart you'll first launch enclave-enabled VMs on Azure using MC² before uploading data and runing computation.

1. Start off in the container you built in the [installation](#installation) section. In the container, copy the contents of the `quickstart` directory to your mounted "playground" directory to ensure that your changes inside the container get reflected on your host. Otherwise, no need to do anything. Then, configure MC² Client with your configuration file.

```sh
# From the /mc2/client directory
cp -r quickstart/* playground
mc2 configure $(pwd)/playground/config.yaml
```

```sh
mc2 init
```

1. Next, launch the machines and resources you'll be using for computation. This step does not exist in the Docker quickstart. MC² Client provides an interface to launch resources on Azure (and sets up the machines with necessary dependencies). Take a look at the `launch` section of the configuration file -- you'll need to specify the path to your [Azure configuration file](quickstart/azure.yaml), which is a YAML file that details the names and types of various resources you will launch.

Next, log in to Azure through the command line and set your subscription ID. [Here](https://docs.microsoft.com/en-us/azure/media-services/latest/setup-azure-subscription-how-to?tabs=portal) are instructions on how to find your subscription ID.

```sh
az login
az account set -s
```
Once you've done that, launch the resources.

```sh
mc2 launch
```

1. Start [Opaque SQL](https://mc2-project.github.io/opaque-sql-docs/src/index.html), a MC² service for secure SQL analytics.

```sh
mc2 start
```

```sh
mc2 upload
```

```sh
mc2 run
```

```sh
mc2 download
```

1. Once you've finished using your Azure resources, you can use MC² Client to terminate them. You can specify which resources to terminate in the `teardown` section of the configuration.

```sh
mc2 teardown
```

## Documentation
For more thorough documentation MC² Client and Opaque SQL, please visit:

* [MC² Client](https://mc2-project.github.io/client-docs/index.html)
* [Opaque SQL](https://mc2-project.github.io/opaque-sql-docs/src/index.html)

## Contact
Join our [Slack](https://join.slack.com/t/mc2-project/shared_invite/zt-rt3kxyy8-GS4KA0A351Ysv~GKwy8NEQ), open a [GitHub issue](https://github.com/mc2-project/mc2/issues), or send a message to [email protected].