QTrojan: A Circuit Backdoor Against Quantum Neural Networks

Cheng Chu, Lei Jiang, Martin Swany, Fan Chen
2/16/2023
quant-phcs.AIcs.CR

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Abstract

We propose a circuit-level backdoor attack, \textit{QTrojan}, against Quantum Neural Networks (QNNs) in this paper. QTrojan is implemented by few quantum gates inserted into the variational quantum circuit of the victim QNN. QTrojan is much stealthier than a prior Data-Poisoning-based Backdoor Attack (DPBA), since it does not embed any trigger in the inputs of the victim QNN or require the access to original training datasets. Compared to a DPBA, QTrojan improves the clean data accuracy by 21\% and the attack success rate by 19.9\%.

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Cite this paper

@article{chu2023qtrojan,
  title  = {QTrojan: A Circuit Backdoor Against Quantum Neural Networks},
  author = {Cheng Chu and Lei Jiang and Martin Swany and Fan Chen},
  year   = {2023},
  eprint = {2302.08090},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2302.08090v1}
}

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