论文标题

使用元图的物联网注入可靠的射频指纹

Injecting Reliable Radio Frequency Fingerprints Using Metasurface for The Internet of Things

论文作者

Rajendran, Sekhar, Sun, Zhi, Lin, Feng, Ren, Kui

论文摘要

在物联网中,数十亿个具有有限资源的设备正在互相通信,安全性已成为影响该技术进步的主要绊脚石。基于数字签名的现有身份验证方案在计算时间,电池电量,带宽,内存和相关硬件成本方面具有与之相关的间接费用。利用基于设备的唯一信息的射频指纹(RFF)可能是物联网的一个有前途的解决方案。但是,由于可靠性低和用户能力降低,传统的RFF已过时了。我们提出的解决方案MetaSurface RF指纹注入(MERFFI)是为了将精心设计的射频指纹注入无线物理层,以提高固定物联网设备的安全性,并以最小的开销。指纹注射是使用在我们的实验室中开发和制造的低成本超面实施的,该指纹旨在在IoT设备进行通信的特定频带中制造小但可检测到的扰动。我们已经进行了全面的系统评估,包括距离,方向,多个通道,在这些通道中,这些指纹的可行性,有效性和可靠性得到了验证。提出的Merffi系统可以轻松地集成到现有的身份验证方案中。对一些最威胁性的无线物理层攻击分析了安全漏洞。

In Internet of Things, where billions of devices with limited resources are communicating with each other, security has become a major stumbling block affecting the progress of this technology. Existing authentication schemes-based on digital signatures have overhead costs associated with them in terms of computation time, battery power, bandwidth, memory, and related hardware costs. Radio frequency fingerprint (RFF), utilizing the unique device-based information, can be a promising solution for IoT. However, traditional RFFs have become obsolete because of low reliability and reduced user capability. Our proposed solution, Metasurface RF-Fingerprinting Injection (MeRFFI), is to inject a carefully-designed radio frequency fingerprint into the wireless physical layer that can increase the security of a stationary IoT device with minimal overhead. The injection of fingerprint is implemented using a low cost metasurface developed and fabricated in our lab, which is designed to make small but detectable perturbations in the specific frequency band in which the IoT devices are communicating. We have conducted comprehensive system evaluations including distance, orientation, multiple channels where the feasibility, effectiveness, and reliability of these fingerprints are validated. The proposed MeRFFI system can be easily integrated into the existing authentication schemes. The security vulnerabilities are analyzed for some of the most threatening wireless physical layer-based attacks.

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