The Uber-Knowledge Assumption: A Bridge to the AGM

The generic-group model (GGM) and the algebraic-group model (AGM) have been exceptionally successful in proving the security of many classical and modern cryptosystems. These models, however, come with standard-model uninstantiability results, raising the question of whether the schemes analyzed under them can be based on firmer standard-model footing. We formulate the uber-knowledge (UK) assumption, a standard-model assumption that naturally extends the uber-assumption family to knowledge-type problems. We justify the soundness of UK in both the bilinear GGM and the bilinear AGM. Along the way we extend these models to account for hashing into groups, an adversarial capability that is available in many concrete groups—In contrast to standard assumptions, hashing may affect the validity of knowledge assumptions. These results, in turn, enable a modular approach to security in the GGM and the AGM. As example applications, we use the UK assumption to prove knowledge soundness of Groth's zero-knowledge SNARK (EUROCRYPT 2016) and of KZG polynomial commitments (ASIACRYPT 2010) in the standard model, where for the former we reuse the existing proof in the AGM without hashing.

Authors

Institutions

Publication Details

Journal
IACR Communications in Cryptology
Published
2024-10-07
DOI
https://doi.org/10.62056/anr-zoja5
Citations
5
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
1.74

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Uber-Knowledge Assumption: A Bridge to the AGM

Patrick Harasser, Pooya Farshim, Balthazar Bauer, Markulf Kohlweiss
5 citations
IACR Communications in Cryptology
Cryptography and Data Security
1.74
article

The Uber-Knowledge Assumption: A Bridge to the AGM

Patrick Harasser, Pooya Farshim, Balthazar Bauer, Markulf Kohlweiss
article en
5 citations

Abstract

The generic-group model (GGM) and the algebraic-group model (AGM) have been exceptionally successful in proving the security of many classical and modern cryptosystems. These models, however, come with standard-model uninstantiability results, raising the question of whether the schemes analyzed under them can be based on firmer standard-model footing. We formulate the uber-knowledge (UK) assumption, a standard-model assumption that naturally extends the uber-assumption family to knowledge-type problems. We justify the soundness of UK in both the bilinear GGM and the bilinear AGM. Along the way we extend these models to account for hashing into groups, an adversarial capability that is available in many concrete groups—In contrast to standard assumptions, hashing may affect the validity of knowledge assumptions. These results, in turn, enable a modular approach to security in the GGM and the AGM. As example applications, we use the UK assumption to prove knowledge soundness of Groth's zero-knowledge SNARK (EUROCRYPT 2016) and of KZG polynomial commitments (ASIACRYPT 2010) in the standard model, where for the former we reuse the existing proof in the AGM without hashing.

IACR Communications in Cryptology
Moog (United States) (US), Durham University (GB), Université de Versailles Saint-Quentin-en-Yvelines (FR), Technische Universität Darmstadt (DE), University of Edinburgh (GB)
Deutsche Forschungsgemeinschaft, Engineering and Physical Sciences Research Council
Partnerships for the goals
Openalex Percentile: Top 13%
Cryptography and Data Security
1.74
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.