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SAGMA: Secure Aggregation Grouped by Multiple Attributes

Summary: SAGMA enables secure aggregation over outsourced data with GROUP BY, supporting arbitrary grouping attributes and protecting cloud ciphertexts semantically. It hides access patterns and group frequencies to curb leakage; evaluation shows feasibility. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5844
Venue
SIGMOD
Year
2020
Pagerank
5.4155107e-05
Overall Rank
8,486 | 41.78%
DOI
10.1145/3318464.3380569

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{hackenjos_sigmod20,
        title = {{SAGMA: Secure Aggregation Grouped by Multiple Attributes}},
        author = {Hackenjos, Timon and Hahn, Florian and Kerschbaum, Florian},
        series = {{SIGMOD} '20},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3318464.3380569},
        url = {https://dl.acm.org/doi/10.1145/3318464.3380569},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
3,131 HEDA: Multi-Attribute Unbounded Aggregation over Homomorphically Encrypted Database 2023 VLDB 7.7249939e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
114 Executing SQL over Encrypted Data in the Database-Service-Provider Model 2002 SIGMOD 0.00032363776
1,310 A Privacy-Preserving Index for Range Queries 2004 VLDB 0.00011209219
2,292 Answering Aggregation Queries in a Secure System Model 2007 VLDB 8.7961091e-05
8,742 Practical and Secure Substring Search 2018 SIGMOD 5.3766157e-05
Previous Page 1 / 1 Next

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