Classical Homomorphic Encryption for Quantum Circuits
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Abstract (arXiv)
We present the first leveled fully homomorphic encryption scheme for quantum circuits with classical keys. The scheme allows a classical client to blindly delegate a quantum computation to a quantum server: an honest server is able to run the computation while a malicious server is unable to learn any information about the computation. We show that it is possible to construct such a scheme directly from a quantum secure classical homomorphic encryption scheme with certain properties. Finally, we show that a classical homomorphic encryption scheme with the required properties can be constructed from the learning with errors problem.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Aug 2017.
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Citing papers per year: 2023: 1; 2024: 2; 2025: 2; 2026: 1.
6 papers.
- 2024Quantum delegated and federated learning via quantum homomorphic encryptioncited by 7
- 2023QuMoS: A Framework for Preserving Security of Quantum Machine Learning Modelcited by 6
- 2024PristiQ: A Co-Design Framework for Preserving Data Security of Quantum Learning in the Cloudcited by 5
- 2025Adversarial Robustness in Distributed Quantum Machine Learningcited by 2
- 2025Trustworthy Quantum Machine Learning: A Roadmap for Reliability, Robustness, and Security in the NISQ Eracited by 1
- 2026Encryptability As a Coordinate Choice: Depth-One Homomorphic Federated Learning of Quantum Neural Networkscited by 0
- 2026Encryptability As a Coordinate Choice: Depth-One Homomorphic Federated Learning of Quantum Neural Networks24 Sep 2026
- 2025Trustworthy Quantum Machine Learning: A Roadmap for Reliability, Robustness, and Security in the NISQ Era4 Nov 2025
- 2025Adversarial Robustness in Distributed Quantum Machine Learning16 Aug 2025
- 2024Quantum delegated and federated learning via quantum homomorphic encryption28 Sep 2024
- 2024PristiQ: A Co-Design Framework for Preserving Data Security of Quantum Learning in the Cloud20 Apr 2024
- 2023QuMoS: A Framework for Preserving Security of Quantum Machine Learning Model23 Apr 2023