解决射频指纹在辐射识别中缺乏便携性的措施

G. Baldini, Raimondo Giuliani, C. Gentile, G. Steri
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引用次数: 11

摘要

射频(RF)无线设备可以通过其发射时产生的射频发射来识别。其原因是,这种发射含有源自物理结构和用于制造无线设备本身的材料的固有特征。这些特征在文献中通常被称为射频指纹,它们可以通过称为辐射识别的过程来唯一地识别无线设备。射频指纹技术可以支持安全应用中无线设备的多因素认证。射频指纹的便携性不足是射频识别中尚未解决的主要问题之一。射频发射由射频接收器收集,将其转换为数字格式,从中提取指纹。缺乏可移植性的问题是由于每个射频接收器引入了一个偏差,这降低了发射设备的射频指纹。因此,由不同射频接收器收集的同一无线设备的射频发射将为同一无线设备产生不同的指纹。这个问题极大地限制了射频指纹识别在安全目的上的适用性,因为我们不能使用不同的射频接收器来执行识别,而且指纹不能从一个接收器移植到另一个接收器。在本文中,我们提出了一种有助于减轻这种可移植性问题的新方法。我们的方法是基于通过使用一个黄金基准来消除射频接收器在频域中引入的偏置。黄金参考被用来产生一个校准函数,然后将其应用于由不同射频接收器从任何其他无线设备收集的射频发射。具体方法针对一组10个物联网(IoT)无线设备(加上黄金参考)和3个RF接收器进行了经验验证。我们的实验证据表明,我们的方法能够以识别精度的轻微下降为代价减轻可移植性问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measures to Address the Lack of Portability of the RF Fingerprints for Radiometric Identification
Radio Frequency (RF) wireless devices can be identified by the RF emissions they produce when transmitting. The reason is that such emissions contain intrinsic features originating from the physical structure and the materials used to build the wireless device itself. These features are usually called RF fingerprints in the literature, and they can be used to uniquely identify a wireless device through a process called radiometric identification. RF fingerprinting can support multifactor authentication of wireless devices in security applications. One of the main unresolved issues in radiometric identification is the lack of portability of the RF fingerprints. The RF emissions are collected by a RF receiver converting them into digital format, from which the fingerprints are extracted. The lack of portability issue is due to the fact that each RF receiver introduces a bias, which degrades the RF fingerprints of the emitting device. As a consequence, RF emissions of the same wireless device collected by different RF receivers will generate different fingerprints for the same wireless device. This issue strongly limits the applicability of RF fingerprinting for security purposes, since we are not afforded to use different RF receivers to perform identification, and the fingerprints are not portable from one receiver to another. In this paper, we propose a novel approach that helps mitigating this portability issue. Our approach is based on the removal of the bias introduced by RF receivers in the frequency domain through the use of one golden reference. The golden reference is used to generate a calibration function, which is then applied to the RF emissions collected by different RF receivers from any other wireless device. The specific approach is empirically validated against a set of ten Internet of Things (IoT) wireless devices (plus the golden reference), and three RF receivers. Our experimental evidence demostrates that our method is able to alleviate the portability issue at the cost of a minor degradation in identification accuracy.
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