Auctioning Time Advantage Optimizes MEV Capture on Automated Market Makers
This research introduces an auction mechanism for transaction time advantage, fundamentally reshaping MEV extraction strategies and enabling AMMs to reclaim value.
Epidemic Consensus for Scalable, Decentralized Blockchain Networks
This research introduces a novel, leaderless epidemic consensus protocol that significantly enhances throughput and latency for large-scale decentralized blockchain systems.
Scaling Zero-Knowledge Proofs with Silently Verifiable Proofs
This research introduces silently verifiable proofs, a novel zero-knowledge system enabling constant communication cost for batch verification, fundamentally enhancing scalable privacy-preserving computation.
Proof of Encryption Eliminates MEV, Securing Private, Fair Blockchain Transactions
Proof of Encryption, via BITE Protocol, cryptographically guarantees transaction privacy and fairness at consensus, enabling secure DeFi and institutional blockchain adoption.
Hierarchical Consensus Enhances Blockchain Scalability and Fault Tolerance
A novel hierarchical consensus algorithm boosts blockchain transaction throughput and reduces latency by balancing workload across dynamic, multi-layered nodes.
Zero-Knowledge Proofs: Transforming Digital Privacy and Computational Integrity
Zero-knowledge proofs enable verifiable computation without revealing data, unlocking private, scalable solutions for diverse digital systems.
Dynamic Committee Rotation Secures Sharded Blockchain Consensus
A novel protocol uses verifiable random functions to dynamically reshuffle sharding committees, fundamentally enhancing blockchain security and throughput.
Oblivious Accumulators Fundamentally Enhance Data Privacy in Decentralized Systems
This research introduces oblivious accumulators, a cryptographic primitive that inherently conceals both elements and set size, enabling truly private decentralized applications.
PolyLink: Decentralized Edge AI for Trustless LLM Inference
PolyLink introduces a blockchain-based platform enabling verifiable large language model inference at the edge, addressing centralization and ensuring computational integrity without substantial overhead.
