Wireless device identification with radiometric signatures

V. Brik, Suman Banerjee, M. Gruteser, Sangho Oh
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引用次数: 768

Abstract

We design, implement, and evaluate a technique to identify the source network interface card (NIC) of an IEEE 802.11 frame through passive radio-frequency analysis. This technique, called PARADIS, leverages minute imperfections of transmitter hardware that are acquired at manufacture and are present even in otherwise identical NICs. These imperfections are transmitter-specific and manifest themselves as artifacts of the emitted signals. In PARADIS, we measure differentiating artifacts of individual wireless frames in the modulation domain, apply suitable machine-learning classification tools to achieve significantly higher degrees of NIC identification accuracy than prior best known schemes. We experimentally demonstrate effectiveness of PARADIS in differentiating between more than 130 identical 802.11 NICs with accuracy in excess of 99%. Our results also show that the accuracy of PARADIS is resilient against ambient noise and fluctuations of the wireless channel. Although our implementation deals exclusively with IEEE 802.11, the approach itself is general and will work with any digital modulation scheme.
无线设备识别与辐射特征
我们设计、实现并评估了一种通过无源射频分析来识别IEEE 802.11帧的源网络接口卡(NIC)的技术。这种技术被称为PARADIS,它利用了在制造时获得的发射器硬件的微小缺陷,即使在其他相同的nic中也存在这些缺陷。这些缺陷是发射机特有的,表现为发射信号的伪影。在PARADIS中,我们测量调制域中单个无线帧的区分伪像,应用合适的机器学习分类工具来实现比之前最知名的方案更高程度的NIC识别精度。我们通过实验证明了PARADIS在区分130多个相同的802.11网卡方面的有效性,准确率超过99%。我们的结果还表明,PARADIS的精度对环境噪声和无线信道的波动具有弹性。虽然我们的实现只处理IEEE 802.11,但该方法本身是通用的,可以与任何数字调制方案一起工作。
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