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A Hidden-Bits Approach to Statistical ZAPs from LWE

Authors:
Eli Bradley , UT Austin
George Lu , UT Austin
Shafik Nassar , UT Austin
Brent Waters , UT Austin and NTT Research
David J. Wu , UT Austin
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Conference: TCC 2025
Abstract: We give a new approach for constructing statistical ZAP arguments (a two-message public-coin statistically witness indistinguishable argument) from quasi-polynomial hardness of the learning with errors (LWE) assumption with a polynomial modulus-to-noise ratio. Previously, all ZAP arguments from lattice-based assumptions relied on correlation-intractable hash functions. In this work, we present the first construction of a ZAP from LWE via the classic hidden-bits paradigm. Our construction matches previous lattice-based schemes by being public-coin and satisfying statistical witness indistinguishability. Moreover, our construction is the first lattice-based ZAP that is fully black-box in the use of cryptography. Previous lattice-based ZAPs based on correlation-intractable hash functions all made non-black-box use of cryptography.
BibTeX
@inproceedings{tcc-2025-36162,
  title={A Hidden-Bits Approach to Statistical ZAPs from LWE},
  publisher={Springer-Verlag},
  author={Eli Bradley and George Lu and Shafik Nassar and Brent Waters and David J. Wu},
  year=2025
}