ZNARKs Enable Efficient Verifiable Computation over Integers
A new polynomial commitment with modular remainder fundamentally simplifies creating succinct arguments for real-world integer arithmetic.
Verifiable Shuffle Function Ensures Fair Transaction Ordering and MEV Neutrality
A Verifiable Shuffle Function cryptographically enforces random transaction ordering, fundamentally neutralizing MEV and securing decentralized sequencing.
Black-Box Commit-and-Prove SNARKs Unlock Verifiable Computation Scaling
Artemis, a new black-box SNARK construction, modularly solves the commitment verification bottleneck, enabling practical, large-scale zero-knowledge machine learning.
Optimal Linear-Time Prover Computation Unlocks Practical Zero-Knowledge Proof Scalability
New zero-knowledge protocols achieve optimal linear-time prover computation, transforming ZKP systems into a practical, scalable primitive for verifiable computation.
Subspace Codes Enable Logarithmic Proof Size Constant Verification Time Commitment
A novel polynomial commitment scheme using subspace codes achieves logarithmic proof size and constant verification, enhancing rollup efficiency.
Post-Quantum Succinct Arguments Secure Verifiable Computation against Quantum Adversaries
This work proves a foundational succinct argument is secure in the Quantum Random Oracle Model, guaranteeing long-term security for verifiable computation.
Linear-Time Post-Quantum SNARKs Achieve Optimal Prover Efficiency
Brakedown introduces the first built linear-time SNARK, achieving optimal O(N) prover complexity for large computations while eliminating trusted setup.
Lattice SNARKs Achieve Quasi-Optimal Efficiency via Novel Vanishing Polynomial Commitment
A new lattice-based commitment scheme enables the first quasi-optimal, quantum-resistant SNARKs, making secure, scalable verifiable computation practical.
Sublinear Zero-Knowledge Proofs Democratize Verifiable Computation on Constrained Devices
A novel proof system reduces ZKP memory from linear to square-root scaling, fundamentally unlocking privacy-preserving computation for all mobile and edge devices.
