Zero-Knowledge AI Inference with High Precision

Artificial Intelligence as a Service (AIaaS) enables users to query a model hosted by a service provider and receive inference results from a pre-trained model. Although AIaaS makes artificial intelligence more accessible, particularly for resource-limited users, it also raises verifiability and privacy concerns for the client and server, respectively. While zero-knowledge proof techniques can address these concerns simultaneously, they incur high proving costs due to the non-linear operations involved in AI inference and suffer from precision loss because they rely on fixed-point representations to model real numbers.

Authors

Institutions

Publication Details

Published
2025-11-19
DOI
https://doi.org/10.1145/3719027.3765056
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Zero-Knowledge AI Inference with High Precision

Haodi Wang, Thang Hoang, Arman Riasi, Rouzbeh Behnia et al.
Adversarial Robustness in Machine Learning
article

Zero-Knowledge AI Inference with High Precision

Haodi Wang, Thang Hoang, Arman Riasi, Rouzbeh Behnia, Viet Vo
article en

Abstract

Artificial Intelligence as a Service (AIaaS) enables users to query a model hosted by a service provider and receive inference results from a pre-trained model. Although AIaaS makes artificial intelligence more accessible, particularly for resource-limited users, it also raises verifiability and privacy concerns for the client and server, respectively. While zero-knowledge proof techniques can address these concerns simultaneously, they incur high proving costs due to the non-linear operations involved in AI inference and suffer from precision loss because they rely on fixed-point representations to model real numbers.

City University of Hong Kong (HK), University of South Florida (US), Swinburne University of Technology (AU), Virginia Tech (US)
Openalex Percentile: Top 81%
Adversarial Robustness in Machine Learning
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Zero-Knowledge AI Inference with High Precision — Haodi Wang, Thang Hoang, et al. · (2025) | TGRS Research Map | TGRS