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Other literature type . 2025
License: CC BY
Data sources: Datacite
ZENODO
Other literature type . 2025
License: CC BY
Data sources: Datacite
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LLM-as-Specification-Judge: Multi-Model Consensus for Trustworthy Cryptographic Verification

Authors: Tarsha Kurdi, Mamone;

LLM-as-Specification-Judge: Multi-Model Consensus for Trustworthy Cryptographic Verification

Abstract

Formal verification of cryptographic implementations using proof assistants like F* and Rocq provides strong mathematical guarantees about code correctness. However, the verification process fundamentally depends on human-written specifications that translate informal standards (e.g., NIST FIPS documents, IETF RFCs) into formal machine-checkable predicates. These specifications constitute a critical component of the Trusted Computing Base (TCB), yet remain vulnerable to human error, ambiguity in natural language interpretation, and subtle logical mistakes. This paper presents Specification Consensus, a novel methodology that employs multiple independent Large Language Models (LLMs) as diverse specification generators, creating an N-version programming paradigm for formal specifications. By generating multiple independent formal specifications from the same authoritative standard and verifying cross-consistency through equivalence proofs, we establish implicit semantic bridges between natural language standards and verified implementations. Key contributions: Identification and characterization of the specification trust problem in formal verification A multi-LLM consensus framework for generating and validating formal specifications Methodology for specification equivalence verification using proof assistants Theoretical analysis of TCB reduction through specification diversity Experimental evaluation on SHA-256, AES-128, and ML-KEM cryptographic primitives Keywords: Formal verification, Trusted Computing Base, Large Language Models, cryptographic specifications, N-version programming, specification synthesis, F*, Rocq, high-assurance cryptography

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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