Cover Image

Quantum delegated and federated learning via quantum homomorphic encryption

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Weikang, Deng, Dong-Ling
Format:	Preprint
Published:	2024
Subjects:	Quantum Physics Cryptography and Security Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Permutational-key quantum homomorphic encryption with homomorphic quantum error-correction
by: Ouyang, Yingkai, et al.
Published: (2022)

Privacy-preserving quantum federated learning via gradient hiding
by: Li, Changhao, et al.
Published: (2023)

Blind quantum machine learning with quantum bipartite correlator
by: Li, Changhao, et al.
Published: (2023)

Unifying communication paradigms in measurement-based delegated quantum computing
by: Wiesner, Fabian, et al.
Published: (2025)

Towards practical secure delegated quantum computing with semi-classical light
by: Bourdoncle, Boris, et al.
Published: (2024)

Verified delegated quantum computation requires techniques beyond cut-and-choose
by: Wiesner, Fabian, et al.
Published: (2026)

Quantum delegation with an off-the-shelf device
by: Broadbent, Anne, et al.
Published: (2023)

An advanced data fabric architecture leveraging homomorphic encryption and federated learning
by: Rieyan, Sakib Anwar, et al.
Published: (2024)

Quantum computing on encrypted data with arbitrary rotation gates
by: Joshi, Mohit, et al.
Published: (2025)

Covert Quantum Learning: Privately and Verifiably Learning from Quantum Data
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)

QuantumLeak: Stealing Quantum Neural Networks from Cloud-based NISQ Machines
by: Fu, Zhenxiao, et al.
Published: (2024)

CopyQNN: Quantum Neural Network Extraction Attack under Varying Quantum Noise
by: Fu, Zhenxiao, et al.
Published: (2025)

Ensuring superior learning outcomes and data security for authorized learner
by: Bang, Jeongho, et al.
Published: (2025)

Enhancing Quantum Security over Federated Learning via Post-Quantum Cryptography
by: Li, Pingzhi, et al.
Published: (2024)

Quantum Adversarial Learning for Kernel Methods
by: Montalbano, Giuseppe, et al.
Published: (2024)

Private and interpretable clinical prediction with quantum-inspired tensor train models
by: Monturiol, José Ramón Pareja, et al.
Published: (2026)

Training quantum machine learning models on cloud without uploading the data
by: He, Guang Ping
Published: (2024)

Security Concerns in Quantum Machine Learning as a Service
by: Kundu, Satwik, et al.
Published: (2024)

Quantum Support Vector Regression for Robust Anomaly Detection
by: Tscharke, Kilian, et al.
Published: (2025)

Quantum Autoencoder for Multivariate Time Series Anomaly Detection
by: Tscharke, Kilian, et al.
Published: (2025)

Hacking Cryptographic Protocols with Advanced Variational Quantum Attacks
by: Aizpurua, Borja, et al.
Published: (2023)

Quantum Adversarial Machine Learning and Defense Strategies: Challenges and Opportunities
by: Yocam, Eric, et al.
Published: (2024)

Hybrid Quantum-Classical Autoencoders for Unsupervised Network Intrusion Detection
by: Rasyidi, Mohammad Arif, et al.
Published: (2025)

Machine Learning Cryptanalysis of a Quantum Random Number Generator
by: Truong, Nhan Duy, et al.
Published: (2019)

Harnessing Inherent Noises for Privacy Preservation in Quantum Machine Learning
by: Ju, Keyi, et al.
Published: (2023)

Evaluating Efficacy of Model Stealing Attacks and Defenses on Quantum Neural Networks
by: Kundu, Satwik, et al.
Published: (2024)

Semisupervised Anomaly Detection using Support Vector Regression with Quantum Kernel
by: Tscharke, Kilian, et al.
Published: (2023)

Adversarial Threats in Quantum Machine Learning: A Survey of Attacks and Defenses
by: Ghosh, Archisman, et al.
Published: (2025)

A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models
by: Wendlinger, Maximilian, et al.
Published: (2024)

Quantum-Hybrid Support Vector Machines for Anomaly Detection in Industrial Control Systems
by: Cultice, Tyler, 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)

Entangled Threats: A Unified Kill Chain Model for Quantum Machine Learning Security
by: Debus, Pascal, et al.
Published: (2025)

QML-PipeGuard: Drift-Aware Behavioral Fingerprinting for Quantum Machine Learning Pipeline Integrity
by: Yeniaras, Esra
Published: (2026)

Anomaly Detection for Real-World Cyber-Physical Security using Quantum Hybrid Support Vector Machines
by: Cultice, Tyler, et al.
Published: (2024)

Q-DPTS: Quantum Differentially Private Time Series Forecasting via Variational Quantum Circuits
by: Chen, Chi-Sheng, et al.
Published: (2025)

Differential Privacy of Quantum and Quantum-Inspired Classical Recommendation Algorithms
by: Li, Chenjian, et al.
Published: (2025)

Information-Theoretic Limits of Quantum Learning via Data Compression
by: Angrisani, Armando, et al.
Published: (2021)

A quantum tug of war between randomness and symmetries on homogeneous spaces
by: Arvind, Rahul, et al.
Published: (2023)

Noise-tolerant learnability of shallow quantum circuits from statistics and the cost of quantum pseudorandomness
by: Wadhwa, Chirag, et al.
Published: (2024)