Presentation
Quantum Properties Trojans (QuPTs) for Attacking QNNs
DescriptionQuantum neural networks (QNN) hold immense potential for the future of quantum machine learning (QML). However, QNN security and robustness remain largely unexplored. In this work, we proposed novel trojan attacks based on the quantum computing properties in a QNN-based binary classifier. Our proposed Quantum Properties Trojans (QuPTs) are based on the unitary property of quantum gates to insert noise and Hadamard gates to enable superposition to develop trojans and attack QNNs. We showed that the proposed QuPTs are significantly stealthier and exert an immensely high impact on quantum circuits' performance, specifically QNNs. To the best of our knowledge, this is the first work on the trojan attack on a fully quantum neural network independent of any hybrid classical-quantum architecture.
Event Type
Networking
Work-in-Progress Poster
TimeMonday, June 236:00pm - 7:00pm PDT
LocationLevel 2 Lobby