Verifiable databases are data storage systems where the integrity and authenticity of stored information can be cryptographically proven. These databases employ cryptographic commitments, such as Merkle trees or authenticated data structures, to allow any observer to confirm that data has not been tampered with or incorrectly reported. This capability is crucial for decentralized applications and supply chain solutions where trust in data integrity is paramount. Verifiable databases enhance transparency and auditability in data management.
Context
Verifiable databases are gaining prominence in blockchain-adjacent technologies and decentralized data storage solutions, addressing the need for provable data integrity. The discussion often revolves around the trade-offs between verifiability, storage efficiency, and query performance. Future applications will likely extend to decentralized identity systems and secure data sharing platforms.
A novel vector commitment scheme achieves sublinear update complexity, fundamentally reducing the overhead for light clients to maintain and verify global blockchain state.
A new vector commitment scheme achieves sublinear complexity for both global update size and local proof updates, solving the stateless client efficiency trade-off.
This new vector commitment scheme fundamentally solves the linear-scaling problem for stateless clients by achieving proven sublinear complexity for state updates.
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