Data Masking in PDFs using NLP and Regex

PDF Redaction Automation

Overview

This project automates the redaction of sensitive information in PDF files. It processes PDFs to obscure sensitive data and saves the redacted versions in a specified output folder. The redaction is achieved through a combination of natural language processing (NLP) and regular expressions to identify and replace sensitive information. End of all it creates a new pdf file automatically

Project Structure

• input_pdfs/: Contains the original PDF files that need to be redacted.

  • Example: input_pdfs/test.pdf

• output_pdfs/: Will hold the redacted PDF files. The filenames will include a _redacted suffix.

  • Example: output_pdfs/test_redacted.pdf

• run.py: The main script for processing PDFs. It reads from input_pdfs, applies redactions, and saves the results to output_pdfs.

• requirements.txt: Lists the required Python libraries for the project.

Main Aim

• Sensitive Data Redaction: Automatically redact sensitive information (e.g., personal identifiers and numbers) from PDFs.

• Automation: Streamline the redaction process for multiple PDFs, ensuring consistency and efficiency.

• Output Management: Save redacted PDFs with a clear naming convention for easy identification.

Setup

1. Clone the Repository:

   git clone https://github.com/omertascioglu/Data-Redact-In-Pdf-Using-Turkish-NLP.git
   cd your-repository