Effective Anomaly Detection in Smart Home by Analyzing Sensor Correlations

Giang-Truong NGUYEN  Van-Quyet NGUYEN  Van-Hau NGUYEN  Kyungbaek KIM  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E104-D   No.2   pp.332-336
Publication Date: 2021/02/01
Publicized: 2020/11/09
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2020EDL8056
Type of Manuscript: LETTER
Category: Dependable Computing
Keyword: 
smart home,  sensors,  anomaly,  spatial correlation,  dependable correlation,  

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Summary: 
In a smart home environment, sensors generate events whenever activities of residents are captured. However, due to some factors, abnormal events could be generated, which are technically reasonable but contradict to real-world activities. To detect abnormal events, a number of methods has been introduced, e.g., clustering-based or snapshot-based approaches. However, they have limitations to deal with complicated anomalies which occur with large number of events and blended within normal sensor readings. In this paper, we propose a novel method of detecting sensor anomalies under smart home environment by considering spatial correlation and dependable correlation between sensors. Initially, we pre-calculate these correlations of every pair of two sensors to discover their relations. Then, from periodic sensor readings, if it has any unmatched relations to the pre-computed ones, an anomaly is detected on the correlated sensor. Through extensive evaluations with real datasets, we show that the proposed method outperforms previous approaches with 20% improvement on detection rate and reasonably low false positive rate.