A hierarchical secure aggregation scheme with arbitrary heterogeneous data assignment achieves optimal two-layer communication loads under information-theoretic security against collusions and dropouts.
Distributed linearly separable computation
2 Pith papers cite this work. Polarity classification is still indexing.
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A cost-preserving transformation enforces information-theoretic secrecy in distributed computing via null-space augmentation of the allocation matrix and shared randomness injection.
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On the Optimality of Hierarchical Secure Aggregation with Arbitrary Heterogeneous Data Assignment
A hierarchical secure aggregation scheme with arbitrary heterogeneous data assignment achieves optimal two-layer communication loads under information-theoretic security against collusions and dropouts.
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Secure Multi-User Linearly-Separable Distributed Computing
A cost-preserving transformation enforces information-theoretic secrecy in distributed computing via null-space augmentation of the allocation matrix and shared randomness injection.