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An End-to-End Multi-Stage Kill-Chain Attack on Quantum Neural Networks: Demonstration on Trapped-Ion Hardware
arXiv
Authors: Cedric Brügmann, Daniel Herr, Daniel Ohl de Mello, Pascal Debus, Maximilian Wendlinger, Kilian Tscharke, Juris Ulmanis, Alexander Erhard, Arthur Schmidt, Fabian Petsch
Year
2026
Paper ID
72459
Status
Preprint
Abstract Read
~2 min
Abstract Words
71
Citations
N/A
Abstract
We demonstrate an end-to-end, multi-stage attack against a quantum neural network (QNN) model that is executed on a trapped-ion quantum computer. Our chain combines side-channel reconnaissance, crosstalk characterization, adversarial example generation, and a physical crosstalk attack that realizes the adversarial perturbation on the device. We cover the full attack chain on ion traps and report the corresponding superconducting-hardware experiments in the appendix. We discuss implications for QaaS providers and hardware mitigations.
Why This Paper Matters
- This paper contributes to the Quantum Networks research area in the Quantum Articles archive.
- It adds a 2026 reference point for readers tracking recent quantum research.
- We demonstrate an end-to-end, multi-stage attack against a quantum neural network (QNN) model that is executed on a trapped-ion quantum computer.
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