Private Inexpensive Norm Enforcement (PINE) VDAF
draft-chen-cfrg-vdaf-pine-02
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| Document | Type |
Expired Internet-Draft
(individual)
Expired & archived
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|---|---|---|---|
| Authors | Junye Chen , Christopher Patton | ||
| Last updated | 2025-08-08 (Latest revision 2025-02-04) | ||
| RFC stream | (None) | ||
| Intended RFC status | (None) | ||
| Formats | |||
| Stream | Stream state | (No stream defined) | |
| Consensus boilerplate | Unknown | ||
| RFC Editor Note | (None) | ||
| IESG | IESG state | Expired | |
| Telechat date | (None) | ||
| Responsible AD | (None) | ||
| Send notices to | (None) |
This Internet-Draft is no longer active. A copy of the expired Internet-Draft is available in these formats:
Abstract
This document describes PINE, a Verifiable Distributed Aggregation Function (VDAF) for secure aggregation of high-dimensional, real- valued vectors with bounded L2-norm. PINE is intended to facilitate private and robust federated machine learning.
Authors
(Note: The e-mail addresses provided for the authors of this Internet-Draft may no longer be valid.)