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tidydp 0.1.0

Initial CRAN Release

This is the first release of tidydp, a tidy-style interface for applying differential privacy to data frames in R.

Core Features

• Differential Privacy Mechanisms
  • Laplace mechanism for pure epsilon-differential privacy
  • Gaussian mechanism for (epsilon, delta)-differential privacy
  • Automatic sensitivity calculations based on data bounds
• Tidy-Style API Functions
  • dp_add_noise(): Add calibrated noise to numeric columns with pipe support
  • dp_count(): Compute differentially private counts with optional grouping
  • dp_mean(): Compute differentially private means with optional grouping
  • dp_sum(): Compute differentially private sums with optional grouping
• Privacy Budget Management
  • new_privacy_budget(): Create and initialize privacy budgets
  • check_privacy_budget(): Verify sufficient budget before operations
  • Automatic budget tracking with basic composition
  • Print method for budget status visualization

Technical Details

• All functions support the magrittr pipe operator (%>%)
• Flexible mechanism selection (Laplace or Gaussian)
• Support for grouped operations using group_by parameter
• Comprehensive error handling and input validation
• Built from scratch without external differential privacy dependencies

Documentation

• Complete function documentation with examples
• Comprehensive README with usage examples
• Full test suite with >95% code coverage
• Example script demonstrating common workflows

Notes

• This package implements differential privacy mechanisms from first principles
• Suitable for statistical analysis with formal privacy guarantees
• Compatible with the tidyverse ecosystem
• Designed for CRAN submission standards

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.