Constant proof size refers to a cryptographic proof system where the size of the proof remains fixed regardless of the complexity or quantity of computations being verified. This property is highly desirable in certain zero-knowledge proof constructions. It allows for efficient verification without increasing data transmission requirements, even for very large statements. Such proofs are particularly useful in environments with bandwidth or storage limitations.
Context
In crypto news, constant proof size is often discussed in relation to scalability improvements for blockchain networks, especially with zero-knowledge rollups. Systems achieving this feature allow for verification of numerous transactions or complex computations with minimal on-chain data posting. This characteristic is a subject of active development, aiming to reduce network congestion and transaction fees. Its successful implementation could substantially accelerate mainstream adoption of decentralized applications.
Mercury, a new pairing-based multilinear polynomial commitment scheme, fundamentally resolves the proof size versus prover time trade-off for scalable verifiable computation.
A new polynomial commitment scheme achieves sublinear prover complexity and constant proof size, dramatically accelerating zero-knowledge computation and scaling.
QEDB is a new protocol that uses specialized cryptographic data structures to verify complex SQL queries on large databases, yielding constant-size proofs.
Cryptographers developed a Distributed Verifiable Random Function with proofs of constant size, eliminating bilinear pairings for faster, pairing-free verification.
Samaritan introduces a multilinear polynomial commitment scheme that achieves the theoretical optimum: linear prover time and constant proof size for scalable verifiable computation.
This new folding scheme aggregates multiple zero-knowledge instances into a single, compact proof, achieving logarithmic-time recursive verification for unprecedented rollup scalability.
A novel Vector Hash Commitment achieves constant-size, transparent proofs, resolving the critical trade-off between ZK-SNARK succinctness and ZK-STARK setup-free security.
This new OR-aggregation technique yields constant-size zero-knowledge proofs, fundamentally unlocking scalable, privacy-preserving data integrity for IoT networks.
A new polynomial commitment scheme enables optimal linear-time prover complexity with a universal, updatable setup, finally resolving the ZK-SNARK trust-efficiency paradox.
Pianist distributes ZKP generation across multiple machines, achieving linear scalability with constant communication overhead, resolving the zkRollup proof bottleneck.
A novel OR-aggregation protocol leverages Sigma protocols to achieve constant proof size and verification time, unlocking scalable, private IoT data integrity.
Introducing the first sublinear memory zero-knowledge proof system, this breakthrough enables verifiable computation on resource-constrained devices, fundamentally scaling ZK adoption.
A novel polynomial commitment scheme achieves cryptographic transparency and logarithmic verification, eliminating the reliance on a trusted setup for scalable zero-knowledge proofs.
SublonK introduces a novel SNARK prover whose runtime scales only with the active circuit, fundamentally optimizing large-scale verifiable computation.
New multi-linear commitment scheme reduces ZK prover complexity to logarithmic time, fundamentally accelerating verifiable computation and on-chain privacy.
This research introduces a novel OR-aggregation technique, fundamentally transforming privacy and verifiable computation efficiency in resource-constrained environments.
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