  Quantum computing (QC) holds tremendous promise in revolutionizing
problem-solving across various domains. It has been suggested in literature
that 50+ qubits are sufficient to achieve quantum advantage (i.e., to surpass
supercomputers in solving certain class of optimization problems).The hardware
size of existing Noisy Intermediate-Scale Quantum (NISQ) computers have been
ever increasing over the years. Therefore, Multi-tenant computing (MTC) has
emerged as a potential solution for efficient hardware utilization, enabling
shared resource access among multiple quantum programs. However, MTC can also
bring new security concerns. This paper proposes one such threat for MTC in
superconducting quantum hardware i.e., adversarial SWAP gate injection in
victims program during compilation for MTC. We present a representative
scheduler designed for optimal resource allocation. To demonstrate the impact
of this attack model, we conduct a detailed case study using a sample
scheduler. Exhaustive experiments on circuits with varying depths and qubits
offer valuable insights into the repercussions of these attacks. We report a
max of approximately 55 percent and a median increase of approximately 25
percent in SWAP overhead. As a countermeasure, we also propose a sample machine
learning model for detecting any abnormal user behavior and priority
adjustment.
