PAO: power-efficient attribution of outliers in wireless sensor networks
Proceedings of the Seventh International Workshop on Data Management for Sensor Networks
Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
CTOD: collaborative tree-based outlier detection in wireless sensor networks
Proceedings of the 10th ACM international symposium on Mobility management and wireless access
Trustworthiness analysis of sensor data in cyber-physical systems
Journal of Computer and System Sciences
Distributed anomaly detection for industrial wireless sensor networks based on fuzzy data modelling
Journal of Parallel and Distributed Computing
Efficient event prewarning for sensor networks with multi microenvironments
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
In-network approximate computation of outliers with quality guarantees
Information Systems
Proceedings of the Fourth Symposium on Information and Communication Technology
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In the field of wireless sensor networks, those measurements that significantly deviate from the normal pattern of sensed data are considered as outliers. The potential sources of outliers include noise and errors, events, and malicious attacks on the network. Traditional outlier detection techniques are not directly applicable to wireless sensor networks due to the nature of sensor data and specific requirements and limitations of the wireless sensor networks. This survey provides a comprehensive overview of existing outlier detection techniques specifically developed for the wireless sensor networks. Additionally, it presents a technique-based taxonomy and a comparative table to be used as a guideline to select a technique suitable for the application at hand based on characteristics such as data type, outlier type, outlier identity, and outlier degree.