Scantoverify

Scantoverify is a term used to describe a methodological approach and supporting tools for ensuring the integrity and provenance of digital records through automated scanning and cryptographic verification. It aims to allow organizations to confirm that captured data, such as scanned documents or streaming data, remains unchanged from its source and can be traced to a verifiable origin.

Core to scantoverify is a pipeline that combines data capture, content extraction, and integrity checks. Capture modules acquire data from physical or digital inputs. OCR and metadata extraction produce a normalized representation. A cryptographic hash (for example SHA-256) is computed and published to a tamper-evident log, potentially a Merkle tree or a blockchain-based ledger. Each record links to a source identity and a timestamp, enabling later verification that the data has not been altered since capture.

Etymology: the term is a portmanteau of scan and verify, and is sometimes written as scantoverify or scan-to-verify in documentation. It emerged in online discussions among digital archivists and data integrity researchers in the mid-2010s and gained broader traction in the 2020s as digital recordkeeping grew more complex.

Applications include archival digitization programs, enterprise document management, supply-chain documentation, e-government records, and healthcare data auditing. In practice, scantoverify seeks to provide auditable proof of integrity and provenance for digital assets, reducing disputes over authenticity.

Limitations and criticisms: effectiveness depends on secure input channels and trusted keys; it can incur processing overhead and storage costs; privacy concerns may arise when raw data is logged; and hash or log integrity depends on the security of the verification infrastructure.

See also: data integrity, digital signature, cryptographic hash, tamper-evident log, OCR, provenance.