QTrojan: A Circuit Backdoor Against Quantum Neural Networks
Indiana University（印第安纳大学）
英文摘要：
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\%.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
