QML-PipeGuard: Drift-Aware Behavioral Fingerprinting for Quantum Machine Learning Pipeline Integrity
arXiv:2605.25066v1 Announce Type: cross Abstract: Quantum machine learning (QML) is moving from research prototypes to deployed cloud services. As QML enters regulated industries, the integrity of the quantum stage becomes a practical concern on two fronts: noisy hardware drifts at the channel level between recalibrations, and an adversary with control over the execution environment can substitute the declared quantum channel with a behaviorally similar but mathematically distinct one. Neither concern is covered by existing QML verification work on pulse-level noise, input drift, input-perturb
Quantum machine learning (QML) is transitioning from theoretical research to practical cloud deployments, necessitating robust integrity and security measures for production environments.
Ensuring the integrity and trustworthiness of quantum computations is critical for the adoption of QML in regulated industries and high-stakes applications, where 'noisy' or malicious hardware can compromise results.
The focus of QML verification is expanding beyond pulse-level noise to include drift-aware behavioral fingerprinting, addressing both hardware instability and potential adversarial manipulation of quantum channels.
- · Quantum cloud service providers with robust security
- · Organizations in regulated industries adopting QML
- · Cybersecurity firms specializing in quantum integrity
- · Developers of quantum hardware diagnostics
- · Adversaries attempting to subtly compromise quantum computations
- · QML deployments without adequate integrity safeguards
- · Organizations reliant on unverified quantum results
Increased trust and accelerated adoption of quantum machine learning in sensitive applications.
Development of industry standards and regulatory compliance frameworks for quantum computing integrity and supply chain security.
The emergence of quantum-specific 'zero trust' architectures that continuously monitor and verify the behavior of quantum hardware and software components.
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Read at arXiv cs.LG