WILMINGTON, Del. — July 20, 2026 — Blockchain Computer Inc. today announced the publication of new research by its founder and chief architect, Justin Malonson, titled “Verifiable Consent in Distributed Systems via AI-Governed Identity and Recursive Zero-Knowledge Proofs.”

The research is publicly available through Zenodo under DOI 10.5281/zenodo.21329009 and can be accessed at https://zenodo.org/records/21329009.

The paper examines a central challenge facing artificial intelligence, decentralized applications, digital identity systems, and autonomous agents: how organizations can verify that meaningful consent was granted without exposing the sensitive personal information used to establish that consent.

Traditional consent systems frequently depend on centralized databases, static agreements, and records that are difficult to independently verify. These systems become increasingly inadequate as AI agents gain the ability to access information, make decisions, execute transactions, and interact with systems on behalf of individuals and organizations.

The proposed framework combines decentralized identifiers, verifiable credentials, artificial intelligence-driven policy enforcement, and recursive zero-knowledge proofs. Together, these technologies create a method for proving that an action was properly authorized while minimizing the disclosure of private identity data.

“Consent must become more than a checkbox stored in a centralized database,” said Justin Malonson, founder and chief architect of Blockchain Computer. “As AI systems become increasingly autonomous, organizations need a way to verify identity, authorization, policy compliance, and consent without unnecessarily exposing the underlying personal information.”

The research introduces a model in which consent can be cryptographically associated with a verified identity, limited to a specific purpose, governed by machine-readable policies, assigned an expiration period, and revoked when authorization conditions change.

Recursive zero-knowledge proofs are used to aggregate and verify multiple authorization conditions while reducing the amount of information that must be revealed. This approach could support privacy-preserving interactions across healthcare, financial services, government systems, autonomous AI, Internet of Things devices, and decentralized networks.

The publication supports Blockchain Computer’s broader development of trust infrastructure for autonomous intelligence. The company is building technology that combines verifiable identity, programmable consent, policy-enforced authorization, privacy-preserving credentials, post-quantum security, distributed systems, and secure edge computing.

About the Author

Justin Malonson is a software engineer, blockchain architect, independent researcher, and founder of Blockchain Computer Inc. His work focuses on distributed systems, digital identity, artificial intelligence governance, privacy-preserving computation, cryptographic protocols, and autonomous computing infrastructure.

About Blockchain Computer

Blockchain Computer Inc. is a deep-technology company developing trust infrastructure for autonomous artificial intelligence, decentralized systems, and secure edge computing. Its architecture is designed to help humans, organizations, devices, and AI agents interact with verifiable identity, authorization, privacy, security, and accountability.

Research publication: https://zenodo.org/records/21329009

Company website: https://blockchaincomputer.com


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The research represents an independently published preprint and should not be described as peer-reviewed unless it is subsequently accepted through a formal peer-review process.