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.
|Title of host publication||Proceedings - 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2018|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||12|
|Publication status||Published - 2018 Jul 19|
|Event||48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2018 - Luxembourg City, Luxembourg|
Duration: 2018 Jun 25 → 2018 Jun 28
|Name||Proceedings - 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2018|
|Other||48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2018|
|Period||18/6/25 → 18/6/28|
Bibliographical noteFunding Information:
ACKNOWLEDGMENTS This work was supported by Samsung Research Funding Center of Samsung Electronics under Project Number SRFC-TB1403-04.
© 2018 IEEE.
All Science Journal Classification (ASJC) codes
- Safety, Risk, Reliability and Quality
- Computer Networks and Communications
- Hardware and Architecture
- Energy Engineering and Power Technology