FHE Breakthrough Achieves Practical Encrypted AI Computation Eighty Times Faster
A novel FHE scheme optimizes encrypted matrix arithmetic, delivering an 80x speedup crucial for practical, privacy-preserving on-chain AI and data analysis.
Sublinear Zero-Knowledge Proofs Democratize Verifiable Computation on Constrained Devices
A novel proof system reduces ZKP memory from linear to square-root scaling, fundamentally unlocking privacy-preserving computation for all mobile and edge devices.
Sublinear Zero-Knowledge Proofs Unlock Ubiquitous Private Computation
A new proof system eliminates ZKP memory bottlenecks by achieving square-root scaling, enabling verifiable computation on all devices.
Collaborative zk-SNARKs Enable Private, Decentralized, Scalable Proof Generation
Scalable collaborative zk-SNARKs use MPC to secret-share the witness, simultaneously achieving privacy and $24times$ faster proof outsourcing.
Sublinear Zero-Knowledge Proofs Democratize Verifiable Computation Scaling
A novel space-efficient tree algorithm reduces ZKP memory requirements from linear to square-root, unlocking verifiable computation on resource-constrained devices globally.
Ika Dwallet: Revolutionizing Cross-Chain Asset Control with Advanced MPC Cryptography
Ika introduces dWallets and 2PC-MPC cryptography, enabling zero-trust, programmable cross-chain asset control without bridging, fundamentally advancing Web3 interoperability.
Multi-Party Computation Evolves for Scalable Blockchain Security
A foundational cryptographic breakthrough enables distributed computation and key management without revealing private inputs, unlocking new frontiers for on-chain privacy and robust security.
Silently Verifiable Proofs Revolutionize Private Aggregation Scalability
Introducing silently verifiable proofs, this research enables constant server-to-server communication for zero-knowledge batch verification, fundamentally advancing privacy-preserving analytics at scale.
Efficient Verifiable Deep Learning Training Using Zero-Knowledge Proofs
Kaizen introduces a zero-knowledge proof system dramatically accelerating verifiable deep learning model training, unlocking privacy-preserving AI at scale.
