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Aegis: A Correlation-Based Data Masking Advisor for Data-Sharing Ecosystems

Summary: Aegis picks masking configurations by minimizing predictive-utility deviation via preserved feature–label correlations, working with limited or no raw data. An IPF-based joint estimator enables MI/chi-square/g3 metrics and fast search for privacy-compliant masks that retain downstream ML accuracy. (summarized by gpt-5-mini on Feb 11 2026)

Paper ID
7353
Venue
SIGMOD
Year
2026
Pagerank
4.1945683e-05
Overall Rank
10,046 | 30.12%
DOI
10.1145/3769757

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