IPR-Service

Description

Intellectual Property Rights (IPR) Service offers various methods to embed and detect IPR in tabular, vector and rasters assets.

For tabular and vector formats, IPR can be embedded in the following means:

1. Adding fictitious entries in random places inside the attributes.
2. Modulating some geometries (vector only), supplementing with points collinear to the geometry vertices. In both cases, embedding is taking place in a random but deterministic way, so that detection is possible given the original asset and the key used for embedding.

For raster format, IPR is embedded:

1. as visible watermark, positioned and placed in a fully customized way.
2. as hidden message. In the latter case, detection is possible, revealing the embedded message (key).

Installation

Dependencies

• Python 3.8
• Running instance of a database
• GEOS library
• PROJ 7
• GDAL 3.1
• Apache Arrow binaries
• PCRE development files

Install package

Install geovaex:

pip install git+https://github.com/OpertusMundi/geovaex

Install service with pip:

pip install git+https://github.com/OpertusMundi/ipr-service.git

Install separately the Python required packages:

pip install -r requirements.txt -r requirements-production.txt

Set environment

The following environment variables should be set:

• FLASK_ENV *: development or production.
• FLASK_APP *: geometry_service (if running as a container, this will be always set).
• SECRET_KEY *: The application secret key. The value of this key should remain the same, in order that detection does not break.
• DATABASE_URI *: engine://user:pass@host:port/database
• WORKING_DIR : The location for storing the session files (default: the system temporary path).
• OUTPUT_DIR *: The location used to store exported files.
• INPUT_DIR *: The location of the input files.
• CORS: List or string of allowed origins (default: *).
• LOGGING_CONFIG_FILE *: The logging configuration file.

Database

A database should have been created in a DataBase server.

Initialize the database, running:

flask init-db

Usage

For details about using the service API, you can browse the full OpenAPI documentation.

Build and run as a container

Copy .env.example to .env and configure (e.g FLASK_ENV variable).

Copy compose.yml.example to compose.yml (or docker-compose.yml) and adjust to your needs (e.g. specify volume source locations etc.).

Build:

docker-compose -f compose.yml build

Prepare the following files/directories:

• ./secrets/secret-key: file needed (by Flask) for signing/encrypting session data.
• ./secrets/database-password: file containing the password for the PostGIS database user.
• ./logs: a directory to keep logs.
• ./temp: a directory to be used as temporary storage.
• ./output: a directory to be used to store exported files.
• ./input: a directory where input files are read from.

Start application:

docker-compose -f compose.yml up

Run tests

Copy compose-testing.yml.example to compose-testing.yml and adjust to your needs. This is a just a docker-compose recipe for setting up the testing container.

Build testing container:

docker-compose -f compose-testing.yml build

Run nosetests (in an ephemeral container):

docker-compose -f compose-testing.yml run --rm --user "$(id -u):$(id -g)" nosetests -v