Dual Encryption Scheme Secures Transaction Privacy and Consensus Efficiency
A novel dual encryption scheme maintains transaction confidentiality while achieving optimal communication complexity, resolving the MEV-resistance efficiency trade-off.
Cryptographic Second Price Auctions Secure Transaction Ordering and Mitigate Adversarial MEV
Encrypting transaction bids via a Cryptographic Second Price Auction formally decouples miner revenue from user incentives, ensuring provably fair block construction.
Decoupling Commitment and Coding Secures Data Availability with Stronger Assurance
A new data availability sampling paradigm commits to uncoded data, using on-the-fly network coding to provide orders of magnitude stronger verification assurance.
Class Group Verifiable Delay Functions Secure Decentralized Time and Unbiasable Randomness
Class Group Verifiable Delay Functions establish provably sequential time-delay, enabling secure, low-energy consensus and unbiasable on-chain randomness.
Constant-Time Polynomial Commitment Unlocks Scalable ZK-SNARK Verification
This new Hyper-Efficient Polynomial Commitment scheme achieves constant-time verification, eliminating the primary bottleneck for on-chain zero-knowledge proof scalability.
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.
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.
Non-Interactive Proofs Cryptographically Secure Proof-of-Stake Long-Range Attacks
Non-interactive epiality proofs establish a bounded trust model, cryptographically securing Proof-of-Stake light clients against historical chain rewrites.
Differential Privacy Guarantees Provable Transaction Ordering Fairness in Distributed Systems
By formally linking Differential Privacy to transaction ordering, this research provides a general, quantifiable cryptographic primitive to eliminate algorithmic bias and mitigate MEV.
