LoRaWAN中攻击感知的无同步数据时间戳
Attack-Aware Synchronization-Free Data Timestamping in LoRaWAN
摘要：
LoRaWAN等低功耗广域网技术有望从地理分布的传感器收集低速率监测数据，其中为传感器数据添加时间戳是一项关键的系统功能。本文考虑了一种基于网关处的信号到达时间对LoRaWAN上行链路数据进行时间戳的免同步方法，该方法很好地匹配LoRaWAN的单跳星形拓扑，并从传输时间戳和始终同步终端设备的时钟中释放带宽。然而，我们表明，这种方法是容易受到{ \em帧延迟攻击}组成的恶意帧冲突和延迟重放。真实实验表明，该攻击可以影响大面积的终端设备，最大可达约$50,000\,\text{m}^2$。从更广泛的意义上说，该攻击威胁到任何需要及时交付LoRaWAN帧的系统功能。为了解决这一威胁，我们提出了一种$\mathsf{LoRaTS}$网关设计，该设计集成了商品LoRaWAN网关和低功耗软件定义的无线电接收器，以跟踪终端设备的固有频率偏差。基于LoRa线性调频扩频调制的分析模型，我们开发了信号处理算法，以高精度估计频率偏差，超出LoRa默认解调的精度。精确的频率偏差跟踪能力能够检测到引入额外频率偏差的攻击。我们还研究并实施了一种更狡猾的攻击，使用先进的无线电设备来消除频率偏差。为了解决这个狡猾的攻击，我们提出了一个伪随机间隔跳频方案，以提高我们的频率偏差跟踪方法。大量的实验表明，我们的方法在部署与真正的影响因素，如温度变化的有效性。
英文摘要：
Low-power wide-area network technologies such as LoRaWAN are promising for collecting low-rate monitoring data from geographically distributed sensors, in which timestamping the sensor data is a critical system function. This paper considers a synchronization-free approach to timestamping LoRaWAN uplink data based on signal arrival time at the gateway, which well matches LoRaWAN's one-hop star topology and releases bandwidth from transmitting timestamps and synchronizing end devices' clocks at all times. However, we show that this approach is susceptible to a {\em frame delay attack} consisting of malicious frame collision and delayed replay. Real experiments show that the attack can affect the end devices in large areas up to about $50,000\,\text{m}^2$. In a broader sense, the attack threatens any system functions requiring timely deliveries of LoRaWAN frames. To address this threat, we propose a $\mathsf{LoRaTS}$ gateway design that integrates a commodity LoRaWAN gateway and a low-power software-defined radio receiver to track the inherent frequency biases of the end devices. Based on an analytic model of LoRa's chirp spread spectrum modulation, we develop signal processing algorithms to estimate the frequency biases with high accuracy beyond that achieved by LoRa's default demodulation. The accurate frequency bias tracking capability enables the detection of the attack that introduces additional frequency biases. We also investigate and implement a more crafty attack that uses advanced radio apparatuses to eliminate the frequency biases. To address this crafty attack, we propose a pseudorandom interval hopping scheme to enhance our frequency bias tracking approach. Extensive experiments show the effectiveness of our approach in deployments with real affecting factors such as temperature variations.
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