Post-quantum SNARKs go transparent. Greyhound by @zksecurityXYZ shows how 👇

@zksecurityXYZ Greyhound is a transparent lattice-based SNARK. It leverages structured lattices, Ajtai commitments, and efficient proof generation techniques.

@zksecurityXYZ The core innovation: replace traditional discrete-log or pairing-based setups with lattice assumptions, targeting post-quantum security while maintaining succinctness and verifiability.

@zksecurityXYZ Key primitive: Ajtai commitment. It uses worst-case hardness of lattice problems (e.g., SIS) to bind committed values. Greyhound deploys it within its polynomial commitment and proof-of-knowledge system.

@zksecurityXYZ Greyhound’s protocol operates over integer lattices. It avoids trusted setup through publicly chosen parameters. Security follows from hardness of lattice problems under quantum adversaries, rather than group‑order assumptions.

@zksecurityXYZ Efficiency: authors report an “efficient construction” for both prover and verifier. While still larger than pairing‑based SNARKs, Greyhound scales with modular operations on vectors/matrices—more amenable to lattice-optimised hardware.

@zksecurityXYZ Verifier performance: constant or logarithmic in circuit size, depending on parameterisation. It relies on sampling and check procedures characteristic of lattice commitments—designed to reduce interactivity and prover overhead.

@zksecurityXYZ Integration angle: Greyhound can adapt into existing SNARK toolchains via modular replacement of commitment scheme. It does not mandate redesign of circuit abstractions, making it pragmatic for post‑quantum transition.

@zksecurityXYZ From a cryptographic standpoint, it demonstrates viability: transparent setup, lattice assumptions, and efficient proof structure. Key questions remain around concrete proof sizes, parameter optimisation, and real‑world implementation performance.

@zksecurityXYZ In short, Greyhound is a lattice‑based SNARK built on Ajtai commitments. It achieves post‑quantum security without trusted setup, aiming for practical proof sizes and verifier efficiency. It offers a roadmap for integrating quantum‑resistant cryptography into existing systems.

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