Cross-technology communication (CTC) technique can realize direct communication among heterogeneous wireless devices (e.g., WiFi, ZigBee, and Bluetooth in the 2.4 G ISM band) without gateway equipment for forwarding, which makes heterogeneous wireless communication more convenient and greatly reduces communication costs. However, compared with the traditional homogeneous network model, CTC technique also makes it easier to implement spoofing attacks in heterogeneous networks. WiFi devices with long communication distances and sufficient energy supply can directly launch spoofing attacks against ZigBee devices, which brings severe security concerns for heterogeneous wireless communications. In this paper, we focus on the CTC spoofing attack, especially spoofing attacks from WiFi to ZigBee and propose a machine learning-based method to detect spoofing attacks for heterogeneous wireless networks by using physical-layer information. First, we model the received signal strength (RSS) data of legitimate ZigBee devices to construct a one-class support vector machine (OSVM) classifier for detecting CTC spoofing attacks depending on the obtained training samples. Then, we simulated CTC spoofing attacks in a live testbed and evaluated the performance of our detection method. Results show that our approach is highly effective in spoofing detection. Even if the distance between the legitimate ZigBee device and WiFi attacker is near each other (i.e., less than 2 m) and does not require a large number of samples, the detection rate and precision of our method are both over 90%. Finally, we employ the OSVM classifier to obtain samples of spoofing attacks and then explore using SVM to further improve the performance of the classifier.

中文翻译：

---

在跨技术通信中使用机器学习进行欺骗攻击检测

跨技术通信（CTC）技术可以实现异构无线设备（如2.4G ISM频段的WiFi、ZigBee、蓝牙）之间的直接通信，无需网关设备进行转发，使异构无线通信更加便捷，大大降低通信成本. 然而，与传统的同构网络模型相比，CTC 技术也使得在异构网络中更容易实施欺骗攻击。通信距离远、能量供应充足的WiFi设备可以直接对ZigBee设备发起欺骗攻击，这给异构无线通信带来了严重的安全隐患。在本文中，我们专注于 CTC 欺骗攻击，特别是从 WiFi 到 ZigBee 的欺骗攻击，并提出了一种基于机器学习的方法，通过使用物理层信息来检测异构无线网络的欺骗攻击。首先，我们对合法 ZigBee 设备的接收信号强度 (RSS) 数据进行建模，以根据获得的训练样本构建一类支持向量机 (OSVM) 分类器，用于检测 CTC 欺骗攻击。然后，我们在实时测试平台中模拟了 CTC 欺骗攻击，并评估了我们检测方法的性能。结果表明，我们的方法在欺骗检测方面非常有效。即使合法的 ZigBee 设备和 WiFi 攻击者之间的距离很近（即小于 2 m）并且不需要大量样本，我们的方法的检测率和精度都在 90% 以上。最后，