Transparent Setup

Definition ∞ A transparent setup refers to an arrangement or system where all relevant information, processes, and rules are openly accessible and verifiable by all participants. In the context of digital assets and blockchain, this typically means that transaction histories, smart contract code, and network parameters are publicly viewable and auditable. Such transparency is a core tenet of decentralized technologies, fostering trust and accountability among users and developers. It allows for independent verification of system operations and outcomes.
Context ∞ The emphasis on transparent setups is a recurring theme in discussions about blockchain governance, smart contract security, and regulatory compliance for digital assets. News frequently reports on projects that adopt open-source development models and make their operational data readily available for public scrutiny. The ongoing dialogue centers on how to balance transparency with necessary privacy considerations, particularly as more complex financial instruments and applications are developed on-chain.

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→Verifiable AI

→Succinct Arguments

→Privacy Preservation

Recursive Zero-Knowledge Secures Private Verifiable AI Model Inference

The new recursive ZK framework allows constant-size proofs for massive AI models, solving the critical trade-off between model privacy and verifiability.

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→Decentralized Finance

→zk-STARKs

→Proof-of-Reserves

Zero-Knowledge Proofs Extend Bitcoin Capabilities for Privacy and Succinct Verification

Applying zk-STARKs to Bitcoin enables private Proof-of-Reserves and trust-minimized light clients, fundamentally expanding the protocol's utility.

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→Data Availability

→Verifiable Computation

→Stateless Clients

Succinct Proximity Arguments Enable Sublinear Verification of Massive Data

A new cryptographic primitive, Succinct Non-interactive Arguments of Proximity (SNAPs), allows verifiers to validate massive datasets by reading only a sublinear number of bits.

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→Verifiable Secret Sharing

→Linear Prover Complexity

→Sublinear Proof Size

Optimal Linear Prover Complexity Revolutionizes Polynomial Commitment Schemes

New PolyFRIM polynomial commitment scheme achieves optimal linear prover complexity, accelerating verifiable computation and distributed consensus.

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→Constant Code Rate

→Cryptographic Primitive

→R1CS Circuit

Linear-Time Post-Quantum SNARKs Revolutionize Verifiable Computation Efficiency

Brakedown introduces a post-quantum, linear-time SNARK by engineering a novel polynomial commitment scheme using linear codes, fundamentally accelerating verifiable computation.

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→Knowledge Soundness

→Succinct Arguments

→Standard Assumptions

Lattice-Based Commitments Achieve Post-Quantum Zero-Knowledge with Transparent Setup

A new lattice-based polynomial commitment provides post-quantum security and a transparent setup, fundamentally advancing trustless, quantum-resistant verifiable computation.

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→Symmetric-Key Cryptography

→Post-Quantum Cryptography

→VOLE-in-the-Head

Post-Quantum Transparent zkSNARKs Achieve Succinct, Trustless, and Efficient Verifiable Computation

Phecda combines new polynomial commitment and VOLE-in-the-Head to deliver the first post-quantum, transparent, and succinct zero-knowledge proof system.

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→Post-Quantum Security

→Polynomial Commitment Scheme

→Lattice Based Problems

SmallWood: Hash-Based Commitments Achieve Post-Quantum Zero-Knowledge for Small Instances

SmallWood introduces a post-quantum, hash-based commitment scheme, dramatically shrinking proof sizes for common, small-scale verifiable computation.

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→Scalable Computation

→Computational Integrity

→Linear Time Proving

Sublinear MPC-in-the-Head Achieves Post-Quantum Zero-Knowledge Proof Efficiency

A novel MPC-in-the-Head construction leverages linear coding to achieve post-quantum security with sublinear proof verification, enabling fast, future-proof computation integrity.

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→Vector Commitments

→Symmetric Key Primitives