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PHY foundation for multi-factor ZigBee node authentication

机译:用于多因素ZigBee节点认证的PHY基础

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摘要

The ZigBee specification builds upon IEEE 802.15.4 low-rate wireless personal area standards by adding security and mesh networking functionality. ZigBee networks may be secured through 128-bit encryption keys and by MAC address access control lists, yet these credentials are vulnerable to interception and spoofing via free software tools available over the Internet. This work proposes a multi-factor PHY-MAC-NWK security framework for ZigBee that augments bit-level security using radio frequency (RF) PHY features. These features, or RF fingerprints, can be used to differentiate between dissimilar or like-model wireless devices. Previous PHY-based works on mesh network device differentiation predominantly exploited the signal turn-on region, measured in nanoseconds. For an arbitrary benchmark of 90% or better classification accuracy, this work shows that reliable PHY-based ZigBee device discrimination can be achieved at SNR ≥ 8 dB. This is done using the entire transmission preamble, which is less technically challenging to detect and is over 1000 times longer than the signal turn-on region. This work also introduces a statistical, pre-classification feature ranking technique for identifying relevant features that dramatically reduces the number of RF fingerprint features without sacrificing classification performance.
机译:ZigBee规范通过添加安全性和网状网络功能,以IEEE 802.15.4低速率无线个人区域标准为基础。 ZigBee网络可以通过128位加密密钥和MAC地址访问控制列表来保护,但是这些凭据很容易通过Internet上的免费软件工具进行拦截和欺骗。这项工作为ZigBee提出了一种多因素PHY-MAC-NWK安全框架,该框架利用射频(RF)PHY功能增强了比特级安全性。这些功能或RF指纹可用于区分不同或相似型号的无线设备。先前基于PHY的网状网络设备区分研究主要利用以纳秒为单位测量的信号开启区域。对于90%或更高分类精度的任意基准,这项工作表明,在SNR≥8 dB时,可以实现可靠的基于PHY的ZigBee设备判别。这是使用整个传输前同步码完成的,从技术上讲,它的检测难度较小,并且比信号开启区域的长度长1000倍以上。这项工作还引入了一种统计,预分类特征分级技术,用于识别相关特征,从而在不牺牲分类性能的情况下大大减少了RF指纹特征的数量。

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