7 papers · 1 filter
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…
Optimizing Quantum Embedding using Genetic Algorithm for QML Applications
Koustubh Phalak, Archisman Ghosh, Swaroop Ghosh
Quantum Embeddings (QE) are essential for loading classical data into quantum systems for Quantum Machine Learning (QML). The performance of QML algorithms depends on the type of Q…
AI-driven Reverse Engineering of QML Models
Archisman Ghosh, Swaroop Ghosh
Quantum machine learning (QML) is a rapidly emerging area of research, driven by the capabilities of Noisy Intermediate-Scale Quantum (NISQ) devices. With the progress in the resea…
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…
The Quantum Imitation Game: Reverse Engineering of Quantum Machine Learning Models
Archisman Ghosh, Swaroop Ghosh
Quantum Machine Learning (QML) amalgamates quantum computing paradigms with machine learning models, providing significant prospects for solving complex problems. However, with the…