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Adversarial Threats in Quantum Machine Learning: A Survey of Attacks and Defenses
Archisman Ghosh, Satwik Kundu, Swaroop Ghosh
Quantum Machine Learning (QML) integrates quantum computing with classical machine learning, primarily to solve classification, regression and generative tasks. However, its rapid…
Adversarial Data Poisoning Attacks on Quantum Machine Learning in the NISQ Era
Satwik Kundu, Swaroop Ghosh
With the growing interest in Quantum Machine Learning (QML) and the increasing availability of quantum computers through cloud providers, addressing the potential security risks as…
Inverse-Transpilation: Reverse-Engineering Quantum Compiler Optimization Passes from Circuit Snapshots
Satwik Kundu, Swaroop Ghosh
Circuit compilation, a crucial process for adapting quantum algorithms to hardware constraints, often operates as a ``black box,'' with limited visibility into the optimization tec…
STIQ: Safeguarding Training and Inferencing of Quantum Neural Networks from Untrusted Cloud
Satwik Kundu, Swaroop Ghosh
The high expenses imposed by current quantum cloud providers, coupled with the escalating need for quantum resources, may incentivize the emergence of cheaper cloud-based quantum s…
Security Concerns in Quantum Machine Learning as a Service
Satwik Kundu, Swaroop Ghosh
Quantum machine learning (QML) is a category of algorithms that employ variational quantum circuits (VQCs) to tackle machine learning tasks. Recent discoveries have shown that QML…