19 citations · 34 across the 10 of their papers we have counts for
11 papers
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…
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…
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…
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…
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…
Evaluating Efficacy of Model Stealing Attacks and Defenses on Quantum Neural Networks
Satwik Kundu, Debarshi Kundu, Swaroop Ghosh
Cloud hosting of quantum machine learning (QML) models exposes them to a range of vulnerabilities, the most significant of which is the model stealing attack. In this study, we ass…
DyPP: Dynamic Parameter Prediction to Accelerate Convergence of Variational Quantum Algorithms
Satwik Kundu, Debarshi Kundu, Swaroop Ghosh
The exponential run time of quantum simulators on classical machines and long queue times and high costs of real quantum devices present significant challenges in the efficient opt…
Quantum Machine Learning for Material Synthesis and Hardware Security
Collin Beaudoin, Satwik Kundu, Rasit Onur Topaloglu +1
Using quantum computing, this paper addresses two scientifically pressing and day-to-day relevant problems, namely, chemical retrosynthesis which is an important step in drug/mater…
Knowledge Distillation in Quantum Neural Network using Approximate Synthesis
Mahabubul Alam, Satwik Kundu, Swaroop Ghosh
Recent assertions of a potential advantage of Quantum Neural Network (QNN) for specific Machine Learning (ML) tasks have sparked the curiosity of a sizable number of application re…
Security Aspects of Quantum Machine Learning: Opportunities, Threats and Defenses
Satwik Kundu, Swaroop Ghosh
In the last few years, quantum computing has experienced a growth spurt. One exciting avenue of quantum computing is quantum machine learning (QML) which can exploit the high dimen…
Quantum-Classical Hybrid Machine Learning for Image Classification (ICCAD Special Session Paper)
Mahabubul Alam, Satwik Kundu, Rasit Onur Topaloglu +1
Image classification is a major application domain for conventional deep learning (DL). Quantum machine learning (QML) has the potential to revolutionize image classification. In a…