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入侵检测量子传感器网络

Intrusion Detection Quantum Sensor Networks.

作者信息

Nagy Marius, Nagy Naya

机构信息

College of Computer Engineering and Science, Prince Mohammad Bin Fahd University, Al-Khobar 31952, Saudi Arabia.

Department of Networks and Communications, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia.

出版信息

Sensors (Basel). 2022 Oct 22;22(21):8092. doi: 10.3390/s22218092.

Abstract

This paper proposes a perimeter detection scheme based on the quantum physical properties of photons. Existing perimeter intrusion detection schemes, if using light, rely on the classical properties of light only. Our quantum sensor network uses the quantum property of spatial superposition of photons, meaning that a photon can simultaneously follow two different paths after going through a beam splitter. Using multiple Mach-Zehnder interferometers, an entire web of paths can be generated, such that one single photon occupies them all. If an intruder violates this web in some arbitrary point, the entire photon superposition is destroyed, the photon does not self-interfere any more and this event is detected by measurements. For one single photon, the intruder detection probability is limited theoretically but can be increased arbitrarily with the usage of a sequence of photons. We show both theoretical bounds as well as practical results of the proposed schemes. The practical results are obtained by simulation experiments on IBM Quantum platforms. The benefits of our quantum approach are: low power, invisibility to potential intruders, scalability and easy practical implementation.

摘要

本文提出了一种基于光子量子物理特性的周界检测方案。现有的周界入侵检测方案若使用光,仅依赖光的经典特性。我们的量子传感器网络利用光子的空间叠加量子特性,这意味着一个光子在通过分束器后可以同时沿着两条不同路径传播。使用多个马赫曾德尔干涉仪,可以生成一个完整的路径网络,使得单个光子能占据所有这些路径。如果入侵者在任意一点破坏了这个网络,整个光子叠加态就会被破坏,光子不再自我干涉,并且这个事件可以通过测量检测到。对于单个光子,理论上入侵者检测概率是有限的,但通过使用一系列光子,检测概率可以任意提高。我们展示了所提方案的理论界限以及实际结果。实际结果是通过在IBM量子平台上的模拟实验获得的。我们的量子方法的优点是:低功耗、对潜在入侵者不可见、可扩展性以及易于实际实现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57e8/9654050/ee393bf188ed/sensors-22-08092-g001.jpg

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