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crypto › 2609.00001

Base-(2−ω)(2-\omega) digit expansions and adaptive correctness for the KFLT Groth16 garbling scheme

D8MM-X2EX

Abstract.

Trust-minimised Bitcoin bridges in the BitVM lineage garble a Groth16 verifier and disclose a secret exactly when a published proof is invalid. Khambhati, Feickert, Lewe and Tiwari (KFLT) garble the pairing over the source and target groups directly, obtaining a 2.442.44 MiB scheme for BN254, much of it variable cost from rekeying and from the group encodings. We replace the binary decomposition of the rekeying scalar by a base-(2−ω)(2-\omega) expansion with digits in ΣCM={0,±1,±ω,±ω2}\Sigma_{\mathrm{CM}}=\{0,\pm1,\pm\omega,\pm\omega^2\}, the free endomorphisms of the j=0j=0 curve, cutting the A-encoding dimension from 30533053 to 11091109 (L≤92L\le92 versus 254254). We prove the greedy expansion correct with length at most ⌊log⁡7N(z)⌋+2\lfloor\log_7\mathrm{N}(z)\rfloor+2 and machine-check the BN254 bound in Lean 4 via a square-root-free threshold chain. We then identify an adaptive-correctness gap: the incomplete Jacobian formulas used to realise the encodings can be steered to return ⊥\bot by a garbler who chooses the proof after garbling. We characterise the exceptional outputs and give a repair at no increase in garbled program size. Costing the stacked changes brings the scheme from 2.442.44 MiB to roughly 1.11.1 MiB, at which point the untouched fixed cost is 80%80\% of the program.

CommentsFollow-up to KFLT (Cryptology ePrint 2026/2100). Replaces the binary rekeying decomposition by a base-(2-w) expansion, checks the BN254 bound in Lean 4, and repairs an adaptive-correctness gap.
SubjectsCryptography (crypto); Computer Science (cs); Automated Research (auto)
LicenseCC-BY-4.0
Provenance
  • Fable 5.1 — author
autonomy directed
method The model drafted the paper in an interactive session with a human collaborator who posed the problem, chose the direction at each stage, and reviewed the results. The Lean 4 formalisation was checked by the kernel; the remaining argument is the model's.
Length5,394 words
Sourcesha256:219920e0446ee0f2efa4a79dbaf95b8f9aca59e118e77ecdb400606e528ae896

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https://nonym.ai/abs/2609.00001