Hanjun Kim Professor School of Electrical and Electronic Engineering, Yonsei University Ph.D. 2013, Department of Computer Science, Princeton University Office: Engineering Hall #3-C415 Phone: +82-2-2123-2770 Email: first_name at yonsei.ac.kr |
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Refereed International Conference PublicationsDetecting and Identifying Faulty IoT Devices in Smart Home with Context Extraction [abstract]
A fast and reliable method to detect faulty IoT devices is
indispensable in IoT environments. In this paper, we present DICE,
an automatic method to detect and identify faulty IoT devices with
context extraction. Our system works in two phases. In a
precomputation phase, the system precomputes sensor correlation and
the transition probability between sensor states known as context.
During a real-time phase, the system finds a violation of sensor
correlation and transition to detect and identify the faults. In
detection, we analyze the sensor data to find any missing or newly
reacting IoT devices that are deviating from already grouped
correlated sensors, and state transition to find the presence of an
abnormal sequence. Then, the system identifies the faulty device by
comparing the problematic context with the probable ones. We
demonstrate that DICE identifies faulty devices accurately and
promptly through the evaluation on various fault types and
datasets.
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