PSP-BRQ: Protecting Search Pattern in Privacy-Preserving Boolean Range Query

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This project implements a distributed data encryption, re-encryption, and query system that involves four key roles: DataOwner, CloudServer 1, CloudServer 2, and Client. These components coordinate via socket communication and Redis events to perform data indexing, encryption, re-encryption, and query processing.

Project Overview

The project provides the following functionalities:

1. Database Setup

   • Creates a SQLite database file named data_object_{object_number}_keyword_{keyword_set_num}.db.
   • Defines a table business_table with columns for business_id, latitude, longitude, and keywords.

2. DataOwner

   • Reads the raw data file (the path is configured via config.ini).
   • Builds keyword and location indexes.
   • Encrypts the index data and sends the encryption keys and data to the CloudServers and Client.

3. CloudServer

   • Receives the encrypted data and performs a two-stage re-encryption process.
   • Coordinates data updates and query request handling, and facilitates communication with the Client.

4. Client

   • Generates query tokens and sends query requests.
   • Receives and decrypts query results, then applies logical operations to obtain the final query object ID.
   • Supports both query result updates and the addition of new objects.

Dataset Building

This section outlines the process for constructing the dataset used in this project. A provided Python script (data/original_data_maker.py) generates a SQLite database containing business objects along with their associated keywords, latitude, and longitude. This dataset is crucial for simulating and evaluating the system.

Purpose

The dataset building process aims to:

• Extract Data: Retrieve business objects (e.g., restaurants, stores) from the Yelp Dataset.
• Select Keywords: Randomly choose keywords from business categories to simulate search behavior.
• Create Database: Store the extracted data in a SQLite database for efficient querying and analysis.

Usage

1. Install Dependencies
   Install the required Python packages:

   pip install -r requirements.txt

2. Download Dataset
   Run the following script to download the Yelp Dataset:

   python data/dataDownload.py

   And you can download the Yelp Dataset from the official repository and place the yelp_academic_dataset_business.json file into the data/yelp_dataset/ directory.

3. Build the Database

   • Original Data Maker:

     python data/original_data_maker.py --object_number 1000 --keyword_set_num 100

   • Update Data Maker:

     python data/update_data_maker.py --object_number 1000 --keyword_set_num 100

   Adjust the parameters:

   • object_number: Number of business objects to include.
   • keyword_set_num: Maximum number of unique keywords to track.

4. Output
   The process produces:

   • A SQLite database file (e.g., data_object_2000_keyword_100.db) containing the business_table.
   • A summary detailing the number of processed entries, successful insertions, and unique keywords.

Configuration

Create or update the config.ini file in the project root to configure the database file paths. For example:

[database]
origin_db_path = data_object_2000_keyword_100.db
update_dp_path = update_data_object_1000_keyword_100.db

Simply modify these paths if you wish to use a different database file.

Running the Project

Ensure that the Redis server is installed (the project uses the redis-server command to start Redis) and then run the main program:

python main.py

This script launches the Redis server, CloudServer 1, CloudServer 2, Client, and DataOwner sequentially. All components communicate via sockets and Redis events.

Considerations

• Ensure that the Redis service is installed and that the redis-server command is available in your system PATH.
• Verify that the database paths specified in config.ini are correct and that the corresponding data files exist.

Contribution

Contributions are welcome! Feel free to submit issues or pull requests to improve and optimize the project.

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The above is the basic description and usage of the project.