pllmR13: SIGMA: Secure GPT Inference with Function Secret Sharing
SIGMA provides FSS-based secure transformer operations and GPU-backed inference with preprocessing. PLLM status: tracked.
Status: tracked
Year: 2024
Authors: Kanav Gupta, Neha Jawalkar, Ananta Mukherjee, Nishanth Chandran, Divya Gupta, Ashish Panwar, Rahul Sharma
External source: SIGMA: Secure GPT Inference with Function Secret Sharing
Source contribution
SIGMA provides FSS-based secure transformer operations and GPU-backed inference with preprocessing.
PLLM perspective
Reproduce the original FSS helpers and complete reference workload. Register softmax, activation, normalization and truncation independently with exact phase contracts.
Resident-share and spectral archives are different constructions, not SIGMA reproductions.
This paper remains tracked. Named modules below are implementation targets, not finished PLLM components; no reproduction, integration, assurance, or matched benchmark is claimed.
The source's boundary remains binding: Two online parties and the dealer model must remain explicit. No implicit substitution into the one-evaluator default.
PLLM modules and documentation
Target module identifiers: protocol.fss, gate.fss_nonlinear, prepare.fss. These identifiers describe scoped work unless this page explicitly links an implementation source. Dependencies: None.
Backlog
This source is assigned to reimplementation priority 8, Full-system comparison targets. Its source-registry order is 13. Follow current gates and unfinished work in the research backlog.
R12: Piranha: A GPU Platform for Secure Computation
Piranha separates device, protocol and application layers for GPU-accelerated secret-sharing computation. PLLM status: tracked.
R14: FuseFSS: Efficient Secure LLM Inference with Function Secret Sharing
FuseFSS targets fusion and efficiency of secure nonlinear/helper operations in FSS-based LLM inference. PLLM status: tracked.