QTrojan: A Circuit Backdoor Against Quantum Neural Networks

• URL: http://arxiv.org/abs/2302.08090v1
• Date: Thu, 16 Feb 2023 05:06:10 GMT
• Title: QTrojan: A Circuit Backdoor Against Quantum Neural Networks
• Authors: Cheng Chu, Lei Jiang, Martin Swany, Fan Chen
• Abstract summary: We propose a circuit-level backdoor attack, textitQTrojan, against Quantum Neural Networks (QNNs) QTrojan is implemented by few quantum gates inserted into the variational quantum circuit of the victim QNN.
• Score: 7.159964195773199
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• 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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