{"paper":{"title":"On the Upload versus Download Cost for Secure and Private Matrix Multiplication","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","cs.DC","math.IT"],"primary_cat":"cs.IT","authors_text":"Ravi Tandon, Wei-Ting Chang","submitted_at":"2019-06-25T17:59:10Z","abstract_excerpt":"In this paper, we study the problem of secure and private distributed matrix multiplication. Specifically, we focus on a scenario where a user wants to compute the product of a confidential matrix $A$, with a matrix $B_\\theta$, where $\\theta\\in\\{1,\\dots,M\\}$. The set of candidate matrices $\\{B_1,\\dots,B_M\\}$ are public, and available at all the $N$ servers. The goal of the user is to distributedly compute $AB_{\\theta}$, such that $(a)$ no information is leaked about the matrix $A$ to any server; and $(b)$ the index $\\theta$ is kept private from each server. Our goal is to understand the fundam"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.10684","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}