Zero-Knowledge Authenticators Decouple Public Blockchain Transparency from Private Policy
Zero-Knowledge Authenticators introduce a primitive for policy-private on-chain authentication, securing complex governance rules without public exposure.
Zero-Knowledge Proof of Training Secures Private Decentralized Federated Learning Consensus
ZKPoT introduces a zk-SNARK-based consensus mechanism that proves model accuracy without revealing private data, resolving the critical privacy-accuracy trade-off in decentralized AI.
NIST Lightweight Cryptography Standard Secures Resource-Constrained Decentralized Systems
The Ascon cryptographic primitive standardizes low-power security, enabling robust, side-channel-resistant data integrity for mass-market IoT and edge-node DLT.
Constant-Cost Batch Verification with Silently Verifiable Proofs
Silently Verifiable Proofs introduce a new zero-knowledge primitive that achieves constant verifier-to-verifier communication for arbitrarily large proof batches, drastically cutting overhead for private computation.
Lattice-Based Polynomial Commitments Achieve Post-Quantum Succinctness and Sublinear Verification
Greyhound is the first concretely efficient lattice-based polynomial commitment scheme, enabling post-quantum secure zero-knowledge proofs with sublinear verifier time.
Asynchronous Verifiable Random Functions Achieve Optimal Leaderless BFT Consensus
AVRFs enable every node to verifiably compute the next proposer locally, eliminating leader election latency and achieving optimal asynchronous speed.
Epochless Batched Threshold Encryption Secures Practical Private Transaction Ordering
BEAT-MEV introduces a novel, epochless Batched Threshold Encryption scheme, eliminating costly MPC setup to enable practical, front-running-resistant private mempools.
Constant-Cost Batch Verification for Private Computation over Secret-Shared Data
New silently verifiable proofs achieve constant-size verifier communication for batch ZKPs over secret shares, unlocking scalable private computation.
Hierarchical Aggregate VRFs Decouple Consensus Scalability from Overhead
Introducing Hierarchical Aggregate Verifiable Random Functions (HAVRFs), a primitive that compresses multiple VRF proofs into a single, constant-size proof, enabling scalable and secure committee-based consensus.
