TrojanNet: Detecting Trojans in Quantum Circuits using Machine Learning. (arXiv:2306.16701v1 [quant-ph])

Quantum computing holds tremendous potential for various applications, but
its security remains a crucial concern. Quantum circuits need high-quality
compilers to optimize the depth and gate count to boost the success probability
on current noisy quantum computers. There is a rise of efficient but
unreliable/untrusted compilers; however, they present a risk of tampering such
as Trojan insertion. We propose TrojanNet, a novel approach to enhance the
security of quantum circuits by detecting and classifying Trojan-inserted
circuits. In particular, we focus …

applications compilers computers computing current high machine machine learning quality quantum quantum computers quantum computing security trojans untrusted