Evaluating Efficacy of Model Stealing Attacks and Defenses on Quantum Neural Networks
Fuente:
arXiv
Saved in:
| Main Authors: | Kundu, Satwik, Kundu, Debarshi, Ghosh, Swaroop |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Adversarial Threats in Quantum Machine Learning: A Survey of Attacks and Defenses
by: Ghosh, Archisman, et al.
Published: (2025)
by: Ghosh, Archisman, et al.
Published: (2025)
Security Concerns in Quantum Machine Learning as a Service
by: Kundu, Satwik, et al.
Published: (2024)
by: Kundu, Satwik, et al.
Published: (2024)
Adversarial Data Poisoning Attacks on Quantum Machine Learning in the NISQ Era
by: Kundu, Satwik, et al.
Published: (2024)
by: Kundu, Satwik, et al.
Published: (2024)
Guardians of the Quantum GAN
by: Ghosh, Archisman, et al.
Published: (2024)
by: Ghosh, Archisman, et al.
Published: (2024)
DyPP: Dynamic Parameter Prediction to Accelerate Convergence of Variational Quantum Algorithms
by: Kundu, Satwik, et al.
Published: (2023)
by: Kundu, Satwik, et al.
Published: (2023)
STIQ: Safeguarding Training and Inferencing of Quantum Neural Networks from Untrusted Cloud
by: Kundu, Satwik, et al.
Published: (2024)
by: Kundu, Satwik, et al.
Published: (2024)
Inverse-Transpilation: Reverse-Engineering Quantum Compiler Optimization Passes from Circuit Snapshots
by: Kundu, Satwik, et al.
Published: (2025)
by: Kundu, Satwik, et al.
Published: (2025)
The Quantum Imitation Game: Reverse Engineering of Quantum Machine Learning Models
by: Ghosh, Archisman, et al.
Published: (2024)
by: Ghosh, Archisman, et al.
Published: (2024)
QuantumLeak: Stealing Quantum Neural Networks from Cloud-based NISQ Machines
by: Fu, Zhenxiao, et al.
Published: (2024)
by: Fu, Zhenxiao, et al.
Published: (2024)
Guess, SWAP, Repeat : Capturing Quantum Snapshots in Classical Memory
by: Kundu, Debarshi, et al.
Published: (2025)
by: Kundu, Debarshi, et al.
Published: (2025)
CopyQNN: Quantum Neural Network Extraction Attack under Varying Quantum Noise
by: Fu, Zhenxiao, et al.
Published: (2025)
by: Fu, Zhenxiao, et al.
Published: (2025)
Quantum-Inspired Analysis of Neural Network Vulnerabilities: The Role of Conjugate Variables in System Attacks
by: Zhang, Jun-Jie, et al.
Published: (2024)
by: Zhang, Jun-Jie, et al.
Published: (2024)
Impact of Error Rate Misreporting on Resource Allocation in Multi-tenant Quantum Computing and Defense
by: Das, Subrata, et al.
Published: (2025)
by: Das, Subrata, et al.
Published: (2025)
Link Stealing Attacks Against Inductive Graph Neural Networks
by: Wu, Yixin, et al.
Published: (2024)
by: Wu, Yixin, et al.
Published: (2024)
DM4Steal: Diffusion Model For Link Stealing Attack On Graph Neural Networks
by: Chen, Jinyin, et al.
Published: (2024)
by: Chen, Jinyin, et al.
Published: (2024)
On Stealing Graph Neural Network Models
by: Podhajski, Marcin, et al.
Published: (2025)
by: Podhajski, Marcin, et al.
Published: (2025)
Quantum Adversarial Machine Learning and Defense Strategies: Challenges and Opportunities
by: Yocam, Eric, et al.
Published: (2024)
by: Yocam, Eric, et al.
Published: (2024)
Application of Quantum Tensor Networks for Protein Classification
by: Kundu, Debarshi, et al.
Published: (2024)
by: Kundu, Debarshi, et al.
Published: (2024)
Hacking Cryptographic Protocols with Advanced Variational Quantum Attacks
by: Aizpurua, Borja, et al.
Published: (2023)
by: Aizpurua, Borja, et al.
Published: (2023)
Using Retriever Augmented Large Language Models for Attack Graph Generation
by: Prapty, Renascence Tarafder, et al.
Published: (2024)
by: Prapty, Renascence Tarafder, et al.
Published: (2024)
Deep-Lock: Secure Authorization for Deep Neural Networks
by: Alam, Manaar, et al.
Published: (2020)
by: Alam, Manaar, et al.
Published: (2020)
Towards Strong Certified Defense with Universal Asymmetric Randomization
by: Hong, Hanbin, et al.
Published: (2025)
by: Hong, Hanbin, et al.
Published: (2025)
Stealing Training Graphs from Graph Neural Networks
by: Lin, Minhua, et al.
Published: (2024)
by: Lin, Minhua, et al.
Published: (2024)
Prompt Stealing Attacks Against Text-to-Image Generation Models
by: Shen, Xinyue, et al.
Published: (2023)
by: Shen, Xinyue, et al.
Published: (2023)
I Stolenly Swear That I Am Up to (No) Good: Design and Evaluation of Model Stealing Attacks
by: Oliynyk, Daryna, et al.
Published: (2025)
by: Oliynyk, Daryna, et al.
Published: (2025)
Transpose Attack: Stealing Datasets with Bidirectional Training
by: Amit, Guy, et al.
Published: (2023)
by: Amit, Guy, et al.
Published: (2023)
Dynamic Quantum Key Distribution for Microgrids with Distributed Error Correction
by: Rath, Suman, et al.
Published: (2024)
by: Rath, Suman, et al.
Published: (2024)
Model Stealing Attack against Graph Classification with Authenticity, Uncertainty and Diversity
by: Zhu, Zhihao, et al.
Published: (2023)
by: Zhu, Zhihao, et al.
Published: (2023)
Hybrid Quantum-Classical Autoencoders for Unsupervised Network Intrusion Detection
by: Rasyidi, Mohammad Arif, et al.
Published: (2025)
by: Rasyidi, Mohammad Arif, et al.
Published: (2025)
GRID: Protecting Training Graph from Link Stealing Attacks on GNN Models
by: Lou, Jiadong, et al.
Published: (2025)
by: Lou, Jiadong, et al.
Published: (2025)
COBRA: Catastrophic Bit-flip Reliability Analysis of State-Space Models
by: Das, Sanjay, et al.
Published: (2025)
by: Das, Sanjay, et al.
Published: (2025)
Backdoor Threats in Variational Quantum Circuits: Taxonomy, Attacks, and Defenses
by: Jiang, Lei, et al.
Published: (2026)
by: Jiang, Lei, et al.
Published: (2026)
A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models
by: Wendlinger, Maximilian, et al.
Published: (2024)
by: Wendlinger, Maximilian, et al.
Published: (2024)
Entangled Threats: A Unified Kill Chain Model for Quantum Machine Learning Security
by: Debus, Pascal, et al.
Published: (2025)
by: Debus, Pascal, et al.
Published: (2025)
AttackGNN: Red-Teaming GNNs in Hardware Security Using Reinforcement Learning
by: Gohil, Vasudev, et al.
Published: (2024)
by: Gohil, Vasudev, et al.
Published: (2024)
GenBFA: An Evolutionary Optimization Approach to Bit-Flip Attacks on LLMs
by: Das, Sanjay, et al.
Published: (2024)
by: Das, Sanjay, et al.
Published: (2024)
Covert Quantum Learning: Privately and Verifiably Learning from Quantum Data
by: Anand, Abhishek, et al.
Published: (2025)
by: Anand, Abhishek, et al.
Published: (2025)
Quantum Privacy Aggregation of Teacher Ensembles (QPATE) for Privacy-preserving Quantum Machine Learning
by: Watkins, William, et al.
Published: (2024)
by: Watkins, William, et al.
Published: (2024)
Q-Detection: A Quantum-Classical Hybrid Poisoning Attack Detection Method
by: He, Haoqi, et al.
Published: (2025)
by: He, Haoqi, et al.
Published: (2025)
Large Language Models for Link Stealing Attacks Against Graph Neural Networks
by: Guan, Faqian, et al.
Published: (2024)
by: Guan, Faqian, et al.
Published: (2024)
Similar Items
-
Adversarial Threats in Quantum Machine Learning: A Survey of Attacks and Defenses
by: Ghosh, Archisman, et al.
Published: (2025) -
Security Concerns in Quantum Machine Learning as a Service
by: Kundu, Satwik, et al.
Published: (2024) -
Adversarial Data Poisoning Attacks on Quantum Machine Learning in the NISQ Era
by: Kundu, Satwik, et al.
Published: (2024) -
Guardians of the Quantum GAN
by: Ghosh, Archisman, et al.
Published: (2024) -
DyPP: Dynamic Parameter Prediction to Accelerate Convergence of Variational Quantum Algorithms
by: Kundu, Satwik, et al.
Published: (2023)