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ZENODO
Other literature type . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Other literature type . 2026
License: CC BY
Data sources: Datacite
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Cryptographically Self-Verifying Systems: Verifiability Without Trusting Any Party

Authors: Juan Rodríguez Monti;

Cryptographically Self-Verifying Systems: Verifiability Without Trusting Any Party

Abstract

This preprint introduces Cryptographically Self-Verifying Systems (CSVS), a system-level design pattern for high-stakes digital processes requiring confidentiality until disclosure, integrity, authenticity, and non-repudiation under fully adversarial backend conditions. CSVS replaces institutional trust with cryptographic evidence, enabling any third party to verify correctness post hoc using only publicly observable artifacts. A central contribution is backend blindness: even a fully malicious backend cannot access or distinguish protected payloads prior to authorized disclosure, enforced by the semantic security of hybrid encryption. We formalize CSVS under a fully adversarial backend model, prove security properties from standard cryptographic assumptions, and introduce low-overhead verifiable relative temporal ordering without trusted clocks, append-only logs, or verifiable delay functions. The paper evaluates security, performance, and limitations, and demonstrates applicability through case studies in vulnerability disclosure, regulatory compliance, and research integrity.

Keywords

transparency, Computer security, zero-day disclosure, Cryptography, verifiability, compliance, post-hoc verification

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green