Dynamic zk-SNARKs Enable Efficient, Incremental Proof Updates for Evolving Data and AI
Dynamic zk-SNARKs introduce incremental proof updates, transforming static verification into adaptable, real-time assurance for evolving AI and blockchain systems.
Novel OR-aggregation Enhances Zero-Knowledge Set Membership for blockchain-IoT
Novel OR-aggregation enables efficient, constant-size zero-knowledge set membership proofs for blockchain-IoT, advancing privacy and scalability.
OR-aggregation Advances Zero-Knowledge Set Membership for Efficient Blockchain Sensor Networks
Novel OR-aggregation optimizes zero-knowledge set membership for blockchain sensor networks, ensuring scalable, privacy-preserving IoT data management.
Novel Formalism Enhances Zero-Knowledge Circuit Verification Scalability and Correctness
A new Prime Field Constraint System (PFCS) formalism and tools enable scalable, compositional verification of zero-knowledge circuits, critical for ZKP security.
STARKs: Scalable, Transparent, Post-Quantum Secure Computational Integrity
This research introduces Scalable Transparent ARguments of Knowledge (STARKs), a cryptographic primitive enabling verifiable computation without trusted setups, ensuring post-quantum security.
OR-aggregation Enhances Zero-Knowledge Set Membership for Scalable IoT Privacy
A novel OR-aggregation technique dramatically improves zero-knowledge set membership efficiency, enabling scalable, private data in IoT blockchain networks.
Merklized Transactions Enhance Blockchain Data Privacy and Granular Scalability
A novel Merkle-based transaction structure enables granular data redaction and lightweight verification, enhancing blockchain privacy and compliance.
Merklized Transactions Enable Granular Data Privacy and Scalable Verification
Merklized transactions redefine blockchain data handling, allowing granular verification and redaction for enhanced privacy and compliance without altering core immutability.
OR-Aggregation Revolutionizes Zero-Knowledge Set Membership for IoT Networks
A novel OR-aggregation technique dramatically improves zero-knowledge set membership proofs, enabling scalable, privacy-preserving data management in resource-constrained IoT environments.
