Inferring User Activities from IoT Device Events in Smart Homes: Challenges and Opportunities
Inferring User Activities from IoT Device Events in Smart Homes: Challenges and Opportunities
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DOI：
10.1109/icccn54977.2022.9868917
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发表时间：
2022-07
期刊：
影响因子：
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通讯作者：
Xuanli Lin;Yinxin Wan;Kuai Xu;Feng Wang;G. Xue
中科院分区：
文献类型：
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作者：
Xuanli Lin;Yinxin Wan;Kuai Xu;Feng Wang;G. Xue
物联网设备在智能家居中的无处不在的部署导致了越来越多的研究兴趣，研究用于各种应用的家庭网络流量，如网络测量、设备分析和物联网设备事件推断。最近的研究表明，可以使用提取的设备事件日志从家庭网络推断用户活动。然而，现有的用户活动推断解决方案，如IoTMosaic和$\Text{E2AP}$，在处理设备故障导致的歧义时存在局限性。本文首先分析了现有用户行为推理算法所面临的挑战，以及它们在某些类型的输入上表现不佳的根本原因。然后，我们表明，即使在设备故障导致用户活动模式不明确的情况下，仍然可以获得有用的信息。我们通过设计对现有算法的扩展来实现这一点。我们还将我们的扩展应用于数字取证应用程序。我们广泛的实验评估表明，尽管存在难以区分的用户活动模式，但我们的解决方案可以有效地为用户活动推理提供洞察力。
The ubiquitous deployment of IoT devices in smart homes has led to growing research interests in studying the home network traffic for various applications such as network measurements, device profiling, and IoT device event inference. Recent studies have shown that user activities can be inferred from a home network using extracted device event logs. However, existing solutions for user activity inference such as IoTMosaic and $\text{E2AP}$ have limitations when handling ambiguities caused by device malfunctions. In this paper, we first identify the challenges faced by the existing user activity inference algorithms and the root causes of their poor performances on certain types of inputs. We then show that useful information can still be obtained even in situations where device malfunctions introduce ambiguities in user activity patterns. We achieve so by designing an extension to the existing algorithms. We also apply our extension in a digital forensics application. Our extensive experimental evaluations demonstrate that our solutions can effectively provide insights to user activity inference despite the presence of indistinguishable user activity patterns.