Trustless Setup refers to a cryptographic system design where the initial parameters or keys are generated in a way that does not require any single entity to be trusted with sensitive information. This ensures that no individual or group can unilaterally compromise the security of the system. It is a critical attribute for decentralized protocols, removing reliance on central authorities or trusted third parties for foundational security. Such setups are essential for maintaining the integrity and impartiality of a system.
Context
The key discussion surrounding trustless setup involves its foundational importance for the security and integrity of zero-knowledge proofs and other privacy-preserving cryptographic protocols in blockchain. Its situation highlights a significant advancement over trusted setup ceremonies, which introduce a single point of potential compromise. A critical future development involves the continued research and implementation of cryptographic techniques that eliminate the need for any form of trusted setup, further enhancing the decentralization and security of digital asset systems.
Artemis CP-SNARK is a modular construction that eliminates the commitment verification bottleneck in zkML, making large-scale, privacy-preserving AI models practical.
A new polynomial commitment scheme achieves sublinear prover complexity and constant proof size, dramatically accelerating zero-knowledge computation and scaling.
This breakthrough cryptographic primitive, based on Groups of Unknown Order, yields a truly succinct zk-SNARK without a trusted setup, unlocking scalable, trustless computation.
A new vector commitment scheme allows light clients to verify massive datasets with logarithmic communication, fundamentally solving the stateless data availability problem.
This new cryptographic primitive formally guarantees committed data is a valid code word, enabling poly-logarithmic Data Availability Sampling without a trusted setup.
A new recursive polynomial commitment scheme, LUMEN, achieves the efficiency of trusted-setup SNARKs while maintaining full transparency, unlocking truly scalable and trustless rollups.
The first complexity-preserving SNARK in the plain model eliminates expensive setup, enabling efficient, publicly verifiable, and composable computation.
Introducing the folding scheme primitive, Nova bypasses complex SNARK recursion, achieving the fastest prover time and a constant-sized verifier circuit for scalable verifiable computation.
FRIDA introduces the first formal cryptographic primitive for Data Availability Sampling, enabling trustless, scalable block data verification for modular blockchains.
A new vector commitment scheme achieves constant verification time with logarithmic proof size, fundamentally enabling efficient stateless clients and scalable data availability.
A new polynomial commitment scheme enables optimal linear-time prover complexity with a universal, updatable setup, finally resolving the ZK-SNARK trust-efficiency paradox.
This new fractal commitment scheme recursively compresses polynomial proofs, achieving truly logarithmic verification costs for universal computation without a trusted setup.
A Distributed Verifiable Random Function combines threshold cryptography and zk-SNARKs to generate public, unpredictable, and bias-resistant randomness.
This research introduces Erasure Code Commitments, a new primitive constructed via a novel IOP compiler, solving data availability without a trusted setup or high overhead.
Fractal introduces a hash-based, transparent SNARK, enabling recursive proofs for quantum-secure, constant-size verification of entire blockchain history.
A novel recursive folding of polynomial commitments into Inner Product Arguments yields universal, transparent proof systems for highly scalable verifiable computation.
Fractal Commitment Schemes introduce a recursive commitment primitive that compresses the universal trusted setup into a constant size, dramatically accelerating verifiable computation deployment.
HyperPlonk introduces a new polynomial commitment scheme, achieving a universal and updatable setup with dramatically faster linear-time proving, enabling mass verifiable computation.
We use cookies to personalize content and marketing, and to analyze our traffic. This helps us maintain the quality of our free resources. manage your preferences below.
Detailed Cookie Preferences
This helps support our free resources through personalized marketing efforts and promotions.
Analytics cookies help us understand how visitors interact with our website, improving user experience and website performance.
Personalization cookies enable us to customize the content and features of our site based on your interactions, offering a more tailored experience.
