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Social Media - Private Set Intersection

Introduction

  • We use a Privacy Enhancing Technology(PET), Private Set Intersection(PSI) to run a intersection check on two datasets and return the common values.
  • Uses the Top 1000 youtuber list from Kaggle, which have been randomly split into two databases.
  • In this project, we develop a POC that allows this phenomenon to run using Openmined's PSI library.

Project Structure

  • This project contains four subdirectories:
    • Server: The server API that performs majority of the PSI computation
    • Client: The client API that retrieves client preferences and queries from the UI, creates a serializable/computable object for the server and returns intersection.
    • Web: The web directory contains source code for the client UI.
    • Data: The data subdirectory contains the intial dataset, that has been split into two subsets uding a 50% row selection probability. It also contains a MongoDB Population script.

Running the APIs

  • Project contains a client and server setup [Both currently Node.js APIs]
  • Prerequisites: Node.js, Python(For running scripts), React(Client Web) and MongoDB
  • Once the prerequisites are installed, we run Taskfile to start our servers

Available Commands

$ ./Taskfile.sh                     # Starts Client, Server and UI concurrently
$ ./Taskfile.sh installAPI          # Installs the dependencies
$ ./Taskfile.sh startUI             # Starts Client UI

Step by Step Run

  • Step 1: To run the client and server, we need to setup the environment variables. Make a copy of .env.example and name the copied file .env and fill in the respective details.
  • Step 2: Install dependencies for both the client, server and the web UI.
$ ./Taskfile.sh installAPI
$ cd web && yarn add
  • Step 3: Once the dependencies are installed, we can run the project.
$ ./Taskfile.sh
  • Step 4: Navigate to localhost:3000 to access the web UI.

Contributors

  • Swadhin Routray
  • Kathryn Earles
  • Wenhan Zhou