A cost-preserving transformation enforces information-theoretic secrecy in distributed computing via null-space augmentation of the allocation matrix and shared randomness injection.
How to share a secret
4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 4representative citing papers
Packed Shamir secret sharing yields up to 11x lower communication and 2.6x faster online runtime for secure deep learning inference versus prior Shamir-based methods.
A quantum anonymous secret sharing scheme is constructed using permutation-invariant codes, with leakage in ramp schemes quantified by quantum conditional min-entropy related to Knill-Laflamme conditions.
ORCHID maps the brain's binding problem to blockchain consensus via Kuramoto oscillators and quantum secret sharing, claiming 100% consensus rates up to 40% Byzantine faults and better message complexity than PBFT in small-network simulations.
citing papers explorer
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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.
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High-Throughput and Scalable Secure Inference Protocols for Deep Learning with Packed Secret Sharing
Packed Shamir secret sharing yields up to 11x lower communication and 2.6x faster online runtime for secure deep learning inference versus prior Shamir-based methods.
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Quantum Anonymous Secret Sharing with Permutation Invariant Codes
A quantum anonymous secret sharing scheme is constructed using permutation-invariant codes, with leakage in ramp schemes quantified by quantum conditional min-entropy related to Knill-Laflamme conditions.
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ORCHID: Orchestrated Reduction Consensus for Hash-based Integrity in Distributed Ledgers
ORCHID maps the brain's binding problem to blockchain consensus via Kuramoto oscillators and quantum secret sharing, claiming 100% consensus rates up to 40% Byzantine faults and better message complexity than PBFT in small-network simulations.