Meaningful Data Erasure in the Presence of Dependencies
Summary: Formalizes data erasure amid database dependencies by requiring that post-erasure inferences about deleted values are no stronger than what could be inferred before insertion. Designs minimally-cost enforcement mechanisms, batching/throughput strategies, proactive retention-time computation, and scalable algorithms. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Vishal Chakraborty (University of California Irvine)
- 2. Youri Kaminsky (Hasso Plattner Institute; University of Potsdam)
- 3. Sharad Mehrotra (University of California Irvine)
- 4. Felix Naumann (Hasso Plattner Institute; University of Potsdam)
- 5. Faisal Nawab (University of California Irvine)
- 6. Primal Pappachan (Portland State University)
- 7. Mohammad Sadoghi (University of California Davis)
- 8. Nalini Venkatasubramanian (University of California Irvine)
BibTeX Citation
@article{chakraborty_vldb25,
title = {{Meaningful Data Erasure in the Presence of Dependencies}},
author = {Chakraborty, Vishal and Kaminsky, Youri and Mehrotra, Sharad and Naumann, Felix and Nawab, Faisal and Pappachan, Primal and Sadoghi, Mohammad and Venkatasubramanian, Nalini},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {10},
pages = {3435--3448},
doi = {10.14778/3748191.3748206},
url = {https://doi.org/10.14778/3748191.3748206},
year = {2025}
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