Polylogarithmic Polynomial Commitment Scheme Unlocks Scalable Verifiable Computation
This new polynomial commitment scheme over Galois rings achieves polylogarithmic verification, fundamentally accelerating zero-knowledge proof systems and verifiable computation.
Sublinear Prover Memory Unlocks Decentralized Verifiable Computation and Privacy Scale
New sublinear-space prover reduces ZKP memory from linear to square-root complexity, enabling ubiquitous on-device verifiable computation and privacy.
Differential Privacy Ensures Fair Transaction Ordering in State Machine Replication
Foundational research links Differential Privacy to equal opportunity in transaction ordering, providing a mathematically rigorous framework to eliminate algorithmic bias and mitigate MEV.
Formalizing Accountable Finality Quantifies Proof-of-Stake Reorganization Economic Cost
The new Accountability Gadget formally quantifies the economic cost of PoS reorganizations, transforming finality from a social consensus into a provable, suicidal economic guarantee.
New Lookup Argument Achieves Optimal Commitment Size for Universal ZK Circuits
Lasso introduces a sparse multilinear polynomial commitment scheme to make non-arithmetic ZK operations linear, unlocking the lookup singularity.
Resumable Zero-Knowledge Proofs Drastically Cut Sequential Verification Cost
A new cryptographic primitive, resumable ZKPoK, enables sequential proof sessions to be exponentially cheaper, unlocking efficient stateful post-quantum cryptography.
Decentralized Proving Markets Secure Verifiable Computation Outsourcing Efficiency
This paper introduces a mechanism design framework for a decentralized proving market, transforming zero-knowledge proof generation into a competitive, economically efficient service.
New Asynchronous Key Generation Protocol Boosts Decentralized Security Efficiency
A novel Asynchronous Distributed Key Generation protocol drastically lowers the computational cost of threshold cryptosystems, enabling robust, fast decentralized key management.
Zero-Knowledge Proof of Training Secures Decentralized Federated Learning
ZKPoT consensus uses zk-SNARKs to verify machine learning contributions privately, resolving the privacy-verifiability trade-off for decentralized AI.
