Design of Quantum Computer Antivirus

Sanjay Deshpande, Chuanqi Xu, Theodoros Trochatos, Hanrui Wang, Ferhat Erata, Song Han, Yongshan Ding, Jakub Szefer
Yale, MIT
(* indicates equal contribution)

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Abstract

The development of quantum computers has been advancing rapidly in recent years. In addition to researchers and companies building bigger and bigger machines, these computers are already being actively connected to the internet and offered as cloud-based quantum computer services. As quantum computers become more widely accessible, potentially malicious users could try to execute their code on the machines to leak information from other users, to interfere with or manipulate results of other users, or to reverse engineer the underlying quantum computer architecture and its intellectual property, for example. To analyze such new security threats to cloud-based quantum computers, this work first proposes and explores different types of quantum computer viruses. This work shows that quantum viruses can impact outcomes of Grover’s search algorithm or machine learning classification algorithms running on quantum computers, for example. The work then proposes a first of its kind quantum computer antivirus as a new means of protecting the expensive and fragile quantum computer hardware from quantum computer viruses. The antivirus can analyze quantum computer programs, also called circuits, and detect possibly malicious ones before they execute on quantum computer hardware. As a compile-time technique, it does not introduce any new overhead at run-time of the quantum computer.

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Citation

@INPROCEEDINGS{10133711,
 author={Deshpande, Sanjay and Xu, Chuanqi and Trochatos, Theodoros and Wang, Hanrui and Erata, Ferhat and Han, Song and Ding, Yongshan and Szefer, Jakub},
 booktitle={2023 IEEE International Symposium on Hardware Oriented Security and Trust (HOST)},
 title={Design of Quantum Computer Antivirus},
 year={2023},
 volume={},
 number={},
 pages={260-270},
 keywords={Computers;Cloud computing;Quantum computing;Machine learning algorithms;Computer viruses;Machine learning;Intellectual property;quantum computers;viruses;quantum computer viruses;antivirus},
 doi={10.1109/HOST55118.2023.10133711}}

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Acknowledgment

This work was supported in part by NSF grants 1901901 and MIT-IBM Watson AI Lab. We would like to thank Dmitrii Kuvaiskii from Intel for help with Intel SGX and Gramine tools.

Team Members