Generalizing Data to Provide Anonymity when Disclosing Information
Summary: Proposes k-anonymity via generalization of quasi-identifiers so each quasi-identifier tuple occurs ≥k times, preventing linkage reidentification. Formalizes generalized tables and minimal generalization; gives algorithm minimizing information loss. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Pierangela Samarati (SRI International)
- 2. Latanya Sweeney (Massachusetts Institute of Technology)
BibTeX Citation
@inproceedings{samarati_pods98,
address = {New York, NY, USA},
series = {{PODS} '98},
title = {{Generalizing Data to Provide Anonymity when Disclosing Information}},
url = {https://dl.acm.org/doi/10.1145/275487.275508},
doi = {10.1145/275487.275508},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Samarati, Pierangela and Sweeney, Latanya},
year = {1998}
}
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