Oblivious Accumulators Enhance Privacy Hiding Set Elements and Size
This work introduces oblivious accumulators, a cryptographic primitive that conceals set elements and size, enabling truly private on-chain data management.
Distributed Cryptographic Accumulators Revolutionize Certificate Revocation Efficiency
AccuRevoke introduces a novel distributed cryptographic accumulator scheme, significantly reducing certificate revocation proof sizes and enhancing PKI scalability and privacy.
Lattice-Based Accumulators Enable Post-Quantum Revocable Anonymous Credentials
This research introduces a novel lattice-based accumulator, offering a post-quantum secure and communication-efficient method for revoking anonymous digital credentials.
Merkle Mountain Ranges Achieve Optimal Witness Updates for Cryptographic Accumulators
This research establishes fundamental lower bounds on cryptographic accumulator witness updates, proving Merkle Mountain Ranges are optimally efficient.
Oblivious Accumulators Conceal Set Elements and Dynamic Changes
This research introduces oblivious accumulators, a novel cryptographic primitive that hides both the elements and the size of a committed set, fundamentally enhancing privacy in decentralized systems.
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.
Eliminating Prime Hashing Makes RSA Accumulators Viable for Decentralized Systems
This new RSA accumulator construction bypasses the slow "hashing into primes" bottleneck, fundamentally enabling succinct, dynamic, and practical set membership proofs on-chain.
Oblivious Accumulators Achieve Private Set Commitments Hiding Elements and Size
Oblivious Accumulators introduce element hiding and update indistinguishability, enabling privacy-preserving set membership proofs for decentralized systems.
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.
