Protected Order Flow Limits Adversarial MEV in Proposer-Builder Separation Systems
PROF enforces transaction ordering within profitable bundles, preventing order manipulation and ensuring timely inclusion in Proposer-Builder Separation.
Zero-Knowledge Proofs Secure Private Decentralized Machine Learning Consensus
A novel Zero-Knowledge Proof of Training consensus mechanism cryptographically validates federated model contributions without exposing private data, enabling scalable and secure decentralized AI.
Encrypted Multi-Scalar Multiplication Privately Outsourced ZK-SNARK Proving
A new cryptographic primitive, Encrypted MSM, offloads zk-SNARK proving complexity to an untrusted server while preserving total witness privacy.
Distributed Proving Architecture Decouples Zero-Knowledge Scaling from Centralized Hardware
This new distributed proving architecture eliminates the zkRollup memory bottleneck, enabling decentralized provers and massive Layer Two scaling.
Universal Composability Framework Unifies Security Analysis for All Layer Two Protocols
The new iUC-based framework models diverse Layer 2 architectures as stateful machines, enabling the first unified, composable security proofs for all scaling solutions.
Block Synchronizer Abstraction Secures BFT Consensus against Network Attacks
The block synchronizer, Beluga, solves BFT performance collapse under attack by coordinating resource-aware, incremental block retrieval.
Cost-Effective Verifiable Delay Functions Unlock Secure EVM Randomness
Optimizing Pietrzak's VDF verification from 4M to 2M gas makes unbiasable on-chain randomness feasible, securing leader election and decentralized applications.
Decoupling BFT Consensus Pacing from Data Dissemination Achieves Optimal Performance
Angelfish introduces a Leader-DAG spectrum consensus, achieving the theoretical optimal latency of leader-based BFT with the peak throughput of DAG protocols.
Formal Verification Quantifies Algorand Consensus Robustness and Adversarial Limitations
Researchers used a process algebraic model and noninterference framework to formally verify Algorand's consensus security, revealing precise adversarial limits.
