De-anonymization Attacks on Neuroimaging Datasets

Summary: De-anonymization of neuroimaging datasets via matrix-based extraction of brain signatures enables cross-dataset re-identification. Scalable preprocessing; tests on public data; discusses privacy risks and defense for sharing neuroimaging. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6187
Venue: SIGMOD
Year: 2021
Pagerank: -
Overall Rank: 13,444 | 7.77%
DOI: 10.1145/3448016.3457234

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Authors

1. Vikram Ravindra (Purdue University)
2. Ananth Grama (Purdue University)

BibTeX Citation

@inproceedings{ravindra_sigmod21,
        title = {{De-anonymization Attacks on Neuroimaging Datasets}},
        author = {Ravindra, Vikram and Grama, Ananth},
        series = {{SIGMOD} '21},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3448016.3457234},
        url = {https://dl.acm.org/doi/10.1145/3448016.3457234},
        year = {2021}
}

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