Quantum-resilient Evidence Structures Ensure Audit Trail Integrity Against Post-Quantum Adversaries

The increasing reliance on artificial intelligence in critical sectors such as healthcare and finance demands robust and verifiable audit trails, and researchers are now addressing the looming threat posed by quantum computers to these systems. Leo Kao from Codebat Technologies Inc, alongside colleagues, investigates how to build evidence structures that remain secure even in a post-quantum world, formalising definitions for quantum audit integrity, non-equivocation, and binding. This work demonstrates that, by leveraging post-quantum signature schemes, it is possible to construct audit trails that resist attacks from powerful quantum adversaries, and importantly, the team explores practical migration strategies for existing audit logs. A case study, conducted using a constant-size evidence platform at Codebat Technologies Inc, reveals that quantum-safe audit trails are achievable with manageable overhead, offering a pathway to extend the long-term reliability of regulated AI deployments.

The study focuses on building systems that can demonstrably prove the integrity of AI operations, a critical requirement for compliance in industries like finance and healthcare. Researchers tackled the challenge of creating audit trails with constant-size evidence packs, ensuring efficient storage and processing of audit data. The team defined new security standards, Q-Audit Integrity, Q-Non-Equivocation, and Q-Binding, specifically tailored to withstand attacks from quantum computers and maintain the trustworthiness of audit logs.

They then analyzed a cryptographic construction, combining hashing and post-quantum digital signatures, proving its security within the quantum random oracle model. This analysis establishes a foundation for building audit trails that remain secure even as quantum computing technology advances. Recognizing the need for practical implementation, the researchers proposed three migration strategies for transitioning existing audit logs to a quantum-safe state. The findings demonstrate that building quantum-safe audit trails is achievable without significant performance overhead. The proposed migration patterns provide a clear roadmap for organizations to upgrade their existing systems and ensure long-term compliance. This work emphasizes the importance of defining security standards specifically for the quantum era and highlights the practical applicability of these solutions in real-world regulated AI environments.

Quantum Audit Integrity for AI Workloads

This study addresses the growing need for cryptographic evidence to support regulated AI workloads, particularly in sectors like clinical trials, pharmaceutical development, and high-stakes finance. Researchers developed a system that generates compact, verifiable records capturing details of code identity, model version, data digests, and platform measurements for each execution step. This work extends this system to account for the threat posed by quantum computers, which could compromise the long-term validity of existing audit logs secured with classical cryptographic methods. Scientists formalized security notions for these evidence structures in a quantum-adversary setting, defining concepts like Q-Audit Integrity, Q-Non-Equivocation, and Q-Binding.

These definitions ensure that an adversary with quantum computational capabilities cannot forge evidence or manipulate past execution records, maintaining the trustworthiness of the audit trail. To achieve quantum resistance, the team analyzed a hash-and-sign construction, leveraging post-quantum signature schemes within the quantum random-oracle model. This analysis demonstrates that, under standard assumptions, the resulting evidence structure satisfies the newly defined security notions, providing a solid foundation for quantum-safe audit trails. Recognizing that many organizations already have substantial investments in existing audit logs, researchers investigated practical migration strategies. They explored combining classical and post-quantum signatures for new evidence, re-signing legacy evidence with post-quantum signatures in a trusted environment, and anchoring legacy data using Merkle roots. Researchers developed a system where each execution step is summarized by a compact, verifiable record encompassing code identity, model version, data digests, and platform measurements. The core achievement lies in extending this system to withstand attacks from quantum computers, a threat to currently used cryptographic methods. Scientists defined new security notions, Q-Audit Integrity, Q-Non-Equivocation, and Q-Binding, to formally capture the requirements for evidence structures in a quantum adversary setting.

These definitions ensure an adversary cannot forge evidence, equivocate on past events, or rebind evidence items, guaranteeing the integrity and trustworthiness of the audit trail. A hash-and-sign construction was then analyzed within the quantum random-oracle model, assuming an underlying post-quantum signature scheme that is existentially unforgeable under chosen-message attacks. This analysis demonstrates that, under standard assumptions, the instantiated scheme satisfies the newly defined quantum-adversary security notions, providing a robust foundation for quantum-safe audit trails. To address existing deployments, the team investigated three migration patterns for evidence logs.

A hybrid approach combining classical and post-quantum signatures for new evidence was examined, alongside re-signing legacy evidence with post-quantum signatures in a trusted environment. Finally, researchers explored Merkle-root anchoring of legacy batches as a means of extending evidentiary lifetime. Each pattern was evaluated based on trust assumptions, security guarantees, and computational and storage overhead. ’s industrial constant-size evidence platform, suggests that securing audit trails against quantum attacks is achievable with moderate overhead. The study demonstrates that systematic migration strategies can significantly extend the evidentiary lifetime of existing deployments, potentially remaining verifiable for a decade or longer.

Post-Quantum Audit Trail Integrity Assured

This research presents a formal analysis of cryptographic evidence structures designed to ensure the integrity of audit trails for regulated artificial intelligence systems, particularly in sensitive fields like healthcare and finance. Scientists developed game-based definitions, Q-Audit Integrity, Q-Non-Equivocation, and Q-Binding, to rigorously assess the security of these evidence records against attacks from quantum computers. Their analysis of a hash-and-sign method, utilising post-quantum signature schemes, demonstrates that these systems can satisfy the defined security properties under established assumptions. The team rigorously defined what it means for an audit trail to be secure against quantum attacks, establishing a formal framework for evaluating the trustworthiness of AI operations.

The analysis provides a strong foundation for building resilient compliance systems, ensuring the integrity of data in critical applications. Furthermore, the team investigated practical strategies for transitioning existing audit logs to post-quantum security, proposing three migration patterns: hybrid signatures, re-signing of older records, and anchoring using Merkle roots. ’s industrial platform, indicates that achieving quantum-safe audit trails is feasible.