Discovering Complex Correlations Among Multiple IoT Devices in Smart Environments
Discovering Complex Correlations Among Multiple IoT Devices in Smart Environments
复制标题
DOI：
10.1109/globecom54140.2023.10437447
复制
发表时间：
2023-12
期刊：
影响因子：
--
通讯作者：
Andrew D’Angelo;Chenglong Fu;Xiaojiang Du;P. Ratazzi
中科院分区：
文献类型：
--
作者：
Andrew D’Angelo;Chenglong Fu;Xiaojiang Du;P. Ratazzi
物联网 (IoT) 在众多消费应用中的普遍性是无与伦比的。不幸的是，尽管物联网有诸多好处，但其广泛集成也带来了重大的安全挑战。考虑到物联网设备与物理环境交互的能力，迫切需要有效的异常检测。最先进的异常检测方法 HAWatcher 通过设备间关联对智能家居的正常行为进行建模，并展示了良好的结果。尽管如此，它仅限于捕获两个事件或状态之间简单的一对一相关性，这削弱了它在更复杂的环境中检测异常的能力。为了解决这个问题，我们提出了一种新颖的相关性发现方法，可以在这种复杂的物联网环境中挖掘复杂的二对一相关性。我们在四个智能家居测试平台上进行了两周的实验，获得了 70 个二对一的相关性。这些相关性适用于 9 个异常场景，与一对一相关性相比，在检测异常方面显示出显着的改进。
The ubiquity of the Internet of Things (IoT) in a vast range of consumer applications is unparalleled. Unfortunately, despite the benefits of IoT, its widespread integration comes with significant security challenges. Considering IoT devices' capability to interact with the physical environment, there is an urgent need for effective anomaly detection. The state-of-the-art anomaly detection method, HAWatcher, models the normal behaviors of smart homes with inter-device correlations and demonstrates great results. Nonetheless, it is limited to capturing only simple one-to-one correlations between two events or states, which undermines its capability to detect anomalies in more complicated environments. To address this issue, we present a novel correlation discovering method to mine complex two-to-one correlations in such complicated IoT-enabled environments. We conduct experiments over two weeks on four smart home testbeds and obtain 70 two-to-one correlations. The correlations are applied to 9 anomaly scenarios, which show significant improvements in detecting anomalies over one-to-one correlations.