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feat: privacy leakage measures (2/6): α-leakage and maximal α-leakage - #82
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Operational definition and Theorem 1 (supremum attained), data processing in both directions, support bounds, zero leakage iff independence, composition, additivity, and I(X;Y) <= L(X->Y) via mutualInfo. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
…Calmon) Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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This library adds support for mathematical verifications of privacy leakage metrics as defined in various established privacy literature. It builds on Statlib's Kernel channels and mutualInfo.
Design issue: #78
Depends on: #79
Formalizes (finite alphabets): Liao, Kosut, Sankar, Calmon, "Tunable measures for information leakage and applications to privacy-utility tradeoffs", arXiv:1809.09231.
How this PR relates to the InfoLeakage library: https://github.com/KoushaKalantari/InfoLeakage#relationship-to-statlib
AI use: I used Opus 5.5 for creating the code, and Codex (gpt-6-astra) for reviewing the proofs.
🤖 Generated with Claude Code