Hanjun Kim  

Associate 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 Publications

Detecting and Identifying Faulty IoT Devices in Smart Home with Context Extraction [abstract]
Jiwon Choi, Hayoung Jeoung, Jihun Kim, Youngjoo Ko, Wonup Jung, Hanjun Kim, and Jong Kim
Proceedings of the 48th IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), June 2018.
Accept Rate: 28% (62/221).

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.