securedai 0.1.1

Secure your ML models using securedai

SecuredAI Python Package

securedai is a Python package designed to easily implement security features for machine learning models or other applications. With simple commands, users can instantiate the package and quickly apply security layers to their models.

Installation

You can install the securedai package using pip:

pip install securedai

Quickstart

Once the package is installed, you can start using it immediately. Here's a simple example:

from securedai import Secured

# Instantiate the Secured class
sc = Secured() 
# Console output: "Constructed secured instance"

# Apply security to 9 models
result = sc.implement(9)
# Console output: "Implemented securety for 9 models!"

print(result)
# Console output: {'status': True, 'message': 'Success'}

Expected Output:

Constructed secured instance
Implemented security for 9 models!    
{'status': True, 'message': 'Success'}

Features

• Easy Security Implementation: Apply security features to any number of models with one command.
• Clear Status Messages: Returns a success message with the status of the security implementation.

Methods

Secured.implement(model_count: int) -> dict

• Description: Implements security for a specified number of models.
• Parameters:
  • model_count (int): The number of models to apply security to.
• Returns:
  • A dictionary with status indicating success or failure, and a message.

Contributing

Feel free to open issues or pull requests if you find any bugs or have feature requests.

License

This project is licensed under the MIT License. See the LICENSE file for details.