Privacy-Preserving Network_Getting Started

Privacy-Preserving Network_Getting Started

Introduction

The Privacy-Preserving Network is a platform to establish the capability for managing the full life cycle of Privacy-Preserving AI, and to suit the requirements of multiple applications, so as to realize the seamless collaboration of technologies (privacy-preserving, blockchain,artificial intelligence, etc) , resources(computing power, data, algorithms, etc) and economic model. It will tackle the problems of data silos, lower the barriers to privacy-preserving AI adoption, and build the next-generation infrastructure of artificial intelligence and digital economy .

Quick Start

Building a privacy-preserving AI project on the Privacy-Preserving Network platform mainly includes the following steps:

  • Login

  • [Data Preparation](#Data Preparation)

  • [Create a Project](#Create a Project)

  • [Create a Workflow](#Create a Workflow)

  • [Model Training](#Model Training)

  • [Model Prediction](#Model Prediction)

  • [Create a Job](#Create a Job)

Logging in

The privacy-preserving platform adopts a decentralized way to manage users. You only need a blockchain wallet that supports MetaMask extension to log in , without registering additional accounts. The steps are as follows:

1、Open the public beta address of the privacy-preserving platform in the Chrome browser: https://39.103.230.158:8443/moirae. Firstly, you need to skip the security verification , please click “Advanced”, and then click "Proceed to 39.103.230.158 (unsafe) ";

2、After entering the page Data Market , and click “Connect Wallet” in the upper right corner ;

3、As the MetaMask installing window pops up, click the button “Install”, follow the prompts to create or import a wallet. You can skip this step if you have already installed it;

  • Note: Metamask extension currently only supports Chrome browser.

4、Click “Connect Wallet” again, after the pop-up window appears, select "I have read and agreed to the “Term of Use” and “Privacy Policy”, then click “MetaMask”;

5、When the “Signature” window pops up, click “Signature” to log in.

Data Preparation

At present, all the available data on the platform is for testing. Users only need to apply for the authorities of the data, which can be used after the data owners accept. Steps as follows:

1、After Logging in, enter the Data Market page, select any data and click “Apply” , then click the “Signature” button after the “Signature” window pops up ;

2、Enter the “Data Application” page, choose the authorization method “Usage Period” or “Usage Count”, select the correspongding value, and then click “Apply”;

3、Open the page"My Resources-Data", you can view the list and authorization status of the data you have applied;

4、When the status changes to “Authorized”, it means the data authorization has succeeded, and the status on the Data Market page will also change to “Authorized”. Now you can use it for [Model Training](#Model Training)。

  • Note: In Privacy-Preserving Computation tasks, it is generally necessary to apply at least two collaborators’ data, one as the “data initiator” (or “data queryer”) and the other as the “data responder” (or “data server”).

Create a Project

“Project” is a module for users to manage Privacy-Preserving Computation tasks. The platform users can create projects based on the Templates page, or independently create a project on the [Projects](https://39.103.230.158:8443/moirae/ project/all) page. The following are steps:

Create on the “Templates” page

1、After entering the Templates page, select one template and click “New Project”;

2、After the “New Project” page is loaded, the corresponding template has been selected by default, enter a project name and a description (not required), and click the “Submit” button to create a new project;

3、On the page" Projects ", click one project name to view its details, the “workflows” page will be loaded defaultly;

4、After the page “Workflows” is displayed, you will see one template has already existed。

Create on the “Projects” page

1、Enter the page " Projects "and click the button “New Project”;

2、Select one template (blank template will create a project without any entities), enter a project name and a description (not required), and click the “Submit” button to create a new project;

3、On the page" Projects ", click one project name to view its details, the “workflows” page will be loaded defaultly;

4、After the page “Workflows” is displayed, you can click “New Workflow” to start construct your project.

Create a Workflow

“Workflow” is the main workspace for constructing and debugging your privacy-preserving computation tasks. Steps as follows:

1、Open the “Workflows” page and click the “New Workflow” button;


2、Enter a “workflow name” and a “workflow description” (not required) , and then click “Submit”.

  • Note: You can also edit the workflow based on the templates directly.

Model Training

You can train privacy-preserving models without any codes in the workflows. The steps are as follows:

1、Click the workflow name selected on the page “Workflows” to view the details;

2、After the page opens, click “Machine Learning” in “My Algorithms” module on the left, expand the list, and click the “Logistic Regression Training” button;

3、The “Logistic Regression Training” node will appear in the center of the page, click it to open its configuration window on the right side;

4、In the node configuration window, click “Input” option, select the “Data Initiator” and “Data responders”, configure the corresponding ID column, labels, features, etc.

  • Note: In privacy logistic regression (vertical) model, the features of the data initiator and the data responders are generally different.

5、Click the “Output” option and choose whether to save to “Data Responders”;

逻辑回归训练节点配置-输出_En

6、Click the “Code” option to view the algorithm codes executed by the current node;

7、Click the “Environment” option, select the minimum requirements for computing resources, including CPU, memory, bandwidth, etc., and then select the “Max Duration”;

  • Note: The system will automatically allocate the best resources to run the task

8、After completing the configuration, click “Start” in the upper right corner of the page, and click “Signature”, then the workflow will start up;

启动工作流_En

9、After the workflow is completed, you can right-click the node “Logistic Regression Training” and click “Result” to view the training result;

逻辑回归训练-右键_En

10、In the pop-up window, you can view the result storage information.

  • Note: The result storage authorization is configured in the node [Output] option. If you are not the data collaborator, there will be no permission to view the result for you.

Model Prediction

You can use the trained privacy-preserving models to predict without any codes in the workflows. The steps are as follows:

1、After completing the [Model Training](#Model Training) step, click the “Logistic Regression Prediction” algorithm;

2、The “Logistic Regression Prediction” node will appear in the center of the page, click it to open its configuration window on the right side;

3、In the node configuration window, click “Input” option, select the “Model” (default is the pre-node output model), “Data Initiator” and “Data Responders”, and configure the corresponding ID column, labels(not required), features, etc;

4、Click the “Output” option and choose whether to save to “Data Responders”;

5、Click the “Code” option to view the algorithm codes executed by the current node;

6、Click the “Environment” option, select the minimum requirements for computing resources, including CPU, memory, bandwidth, etc., and then select the “Max Duration”;;

7、After completing the configuration, click “Start” in the upper right corner of the page, and click “Signature”, then the workflow will start up;

启动工作流_En

8、After the workflow is completed, you can right-click the node “Logistic Regression Prediction” and click “Result” to view the prediction result;

逻辑回归预测-右键_En

9、In the pop-up window, you can view the result storage information。

  • Note: The result storage authorization is configured in the node [Output] option. If you are not the data collaborator, there will be no permission to view the result for you。

Create a Job

Jobs are used to execute and monitor schedule tasks. Steps as follows:

1、On the page " Projects ", click any project name to enter its details pages (the “Workflow” page will be opened by default);

2、Select “Jobs” option and Click “New Job”;

3、In the pop-up window,click “Associated Workflow”,and select a workflow for the schedule task;

5、Select the “Basic Info.” configuration option, enter a “Name” and a “Description” (optional);

6、Select “Schedule” option, choose “Start Time”, “Repeat” Frequency, “End Time”, then click the "Create"button to start the job;

7、On the page " Jobs ", select one job name, you can view the running status of its sub-jobs。

1 Like

被挡在第一步了。。。。
话说,能不能整个域名,并且ssl能访问啊。。。

1 Like

目前内测还没有启用域名,正式开放会调整为https+域名的

公测版本只能键盘输入”thisisunsafe"来解决了

是在市政车库中准备工作的车辆的项目工作示例

After learning about Platon from the contact, I was deeply optimistic about the prospects of the project, through this internal test, let me better understand the privacy protection options, whether it is bank data, medical health, public services, transportation, insurance, etc. A series of personal information, in the current society, have a profound impact on individuals, bad companies collected data from each of us, made some bad things, which is deeply disgusting to me, supporting the Platon network to continue to move forward, Good development, I wish the 2022 Platon network a faster forward, so that more of our people experience the importance of protecting personal privacy

1 Like

Thank you for your trust, PlatON looks forward to your support and contribution

1 Like

indeed an undeniably successful project in the making. surely, platON will break the bounds and become limitless in this community!

3 Likes


Could anyone tell me about how to add Data Responders? It keeps grey and cannot be added.
When I then added Data Responders first, Data Initiator cannot be added.

1 Like

The 0.2.0 beta test is over!

Guys, our Privacy-preserving Network 0.2.0 beta test has come to an end. Thank you very much to our community for your active participation and valuable suggestions during this beta test! We’ve taken all of your suggestions as valuable comments and requests and will reflect them in version 0.3.0.

0.2.0 test reward list

  1. Valuable suggestions were motivated by the following students who made valuable suggestions and received test rewards (ranging from 200-2000 lat)

@202xxx (please reply to my lat address)
@nickyang
@SolidStake (please reply to my lat address)
@LeShallowAh
@yibei

  1. Successfully participated in the calculation of the address (divide 5000LAT)

0xee7233dbb290d486f959bf047f7194a131500e54
0x86245049dae207c9140ee54f21cccdaee7128d99
0x10c072b6ffcd688f1f7bac8fd045a0a6d50b8794
0x7a96b2d957a287d56b32d366e15661a932caf632
0xebef067f32413ec22e0c04f3e9df3d6bf38aa917
0x0af1d4984b3bac8efbf5cd0f86e64fb9d97d06ae
0xe76ca09151f4d825d621d15e37cba364af1ab6c6
0xe15f97799b5c51d1d7bb6736f9a7eec119f19e89
0xc178366aa42052e90644012e7e09920403f2385f
0x016a55f0310590d6714a8839421339ada774e2e1
0x8ba89bf58de1f28fa5d2942f21c55e4e09220d9d
0x2b640fe01f76df7000955a37dab8f2a172acf34d
0x79d1ca86ee44701f70bae5bb1283b54659c3e188
0x671e50800603ff0da7b68ca4c5ce9aae8d36acf0
0x47f22ae47be3237b5161fe3f8362a52db4086ca1
0xd852d5972b166a2424b817803671562a2ea810a9
0x76ef64d131bffde2ae9b651ad6c7f80f0fd67d09
0x886693b61ad0b0873cfef853052692c35fe7e213
0xe69ed8c8652128a2570d82b7d167aa7cff735064
0x05d1d59ac1aa99083759e1dde4b29675860815f4

Thank you to the above peeps for contributing to this test! Rewards will be issued within 7 working days

Preview 0.3.0

According to my snooping, Privacy Computing Network version 0.3.0 is expected to be available to the community in mid-February for testing. If you have any features you would like to see implemented, or ideas you would like to suggest, please reply to us.
Anti-skipping: The exact opening time is subject to the test details of version 0.3.0 :slight_smile:

A series of personal information, in the current society, have a profound impact on individuals, bad companies collected data from each of us, made some bad things, which is deeply disgusting to me, supporting the Platon network to continue to move forward, Good development, I wish the 2022 Platon network a faster forward, so that more of our people experience the importance of protecting personal privacy