Data Anonymizer

The Data Anonymizer is a command-line tool written in Go that anonymizes sensitive data in CSV files. It supports various anonymization techniques for specified columns and generates a new CSV file with anonymized data.

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Features

• Input CSV Support: Accepts a CSV file with column headers as input.

• Anonymization Techniques:

  • Masking: Replaces sensitive data with partial data or asterisks.
  • Pseudonymization: Replaces data with random placeholders.
  • Hashing: Applies irreversible hashing (e.g., SHA-256).
  • Generalization: Broadens specific values into categories.
  • Phone Masking: Masks phone numbers, keeping the first three digits and masking the rest.

• Customizable: Specify columns and techniques via command-line arguments.

• Logging: Logs anonymization activities for transparency.

• Security: Avoids storing sensitive data in memory longer than necessary.

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Installation

Prerequisites

• Go installed (version 1.20+).
• A Linux environment with a terminal (works on macOS and Windows as well).

Steps

1. Clone the repository:

   git clone https://github.com/computerscienceiscool/anonymizer.git
   cd anonymizer

2. Build the executable:

   go build -o anonymizer

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Usage

Command-Line Arguments

Argument	Description
--input	Path to the input CSV file.
--columns	Comma-separated list of columns to anonymize.
--techniques	Comma-separated list of anonymization techniques.
--help	Displays usage information.

Supported Anonymization Techniques

Technique	Description
mask	Replace data with partial information or asterisks.
pseudonymize	Replace data with random placeholders (e.g., "Person 1").
hash	Apply irreversible hashing (e.g., SHA-256).
generalize	Replace numeric data with broader categories (e.g., 29 → "20-29").
phone_mask	Keep the first three digits of a phone number, masking the rest (e.g., 555-****).

Example Command

./anonymizer --input test_data.csv --columns "Name,Email,Phone" --techniques "mask,hash,phone_mask"

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Example Input

Name,Email,Age,Phone
John Doe,john.doe@example.com,29,555-1234
Jane Smith,jane.smith@example.com,34,555-5678

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Example Output

Name,Email,Age,Phone
Jo******,836f82db99121b3481011f16b49dfa5fbc714a0d1b1b9f784a1ebbbf5b39577f,29,555-****
Ja********,f2d1f1c853fd1f4be1eb5060eaae93066c877d069473795e31db5e70c4880859,34,555-****

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Development

Adding Anonymization Techniques

New anonymization techniques can be added by modifying the anonymize function in main.go. Ensure each technique is properly tested.

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Future Improvements

• Support for additional file formats (e.g., Excel, JSON).
• Interactive mode for column selection and technique assignment.
• Batch processing for multiple files.

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License

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