Data Anonymizer

Anonymize sensitive data in your datasets. It generates pseudonyms for specified columns in a CSV file using a salted SHA-256 hashing function. Integrity checks with HMAC. The script allows for reverting the data back to its original form using encrypted mapping files that are generated during the anonymization process.

How It Works

• Load or Generate Secret Key (if not exist)
  • Key should be base64-encoded 32 bytes (256 bits) long
• Process Input Data File
• Data Pseudonymization or Reversion
• Encrypted Mapping Files
  • During the anonymize operation, for each specified column, the script creates an encrypted file that maps the pseudonyms back to the original data.
  • These mapping files are encrypted using the Fernet symmetric encryption scheme, and an HMAC is appended to ensure data integrity.
• Data Integrity
  • When reverting data, the script first checks the integrity of the encrypted mapping files by comparing a stored HMAC with a computed HMAC.
• Output

Install dependencies

pip3 install -r requirements.txt

How to Use

python3 anonymizer.py file_path operation --cols column_names --key_path secret_key_path

• file_path: Path to the data file (CSV format)
• operation: anonymize or revert
• --cols: Specific columns to anonymize or revert (all columns by default)
• --key_path: Path to the secret key file (required)

Usage Example

1. Generate a data example

python3 data.py

3. Anonymize

python3 anonymizer.py data.csv anonymize --key_path secret_key.key

3. Revert

python3 anonymizer.py data.csv revert --key_path secret_key.key

Security

• Secret Key Storage - ensure the secret key file is stored securely. If compromised, an attacker could decrypt the pseudonym mappings and de-anonymize the data.
• Encrypted Mapping Files - ensure that these files are stored in a secure location with restricted access. Access to these files and the secret key allows data de-anonymization.