Abstract
Outliers in wireless sensor networks are measurements that deviate from the normal model of sensed data and result from errors, events or malicious attacks on the network. The dynamic nature of sensor data and the specificity of the wireless sensor network make traditional outlier detection techniques unsuitable for direct application in such contexts so it is essential to select and adapt appropriate techniques to implement in wireless sensor networks for better sensing quality and more reliable system. This paper provides a comprehensive overview of existing outlier detection techniques specifically developed for the wireless sensor networks. Additionally, it presents a technique-based taxonomy to be used as a guideline to select a suitable technique for the application at hand based on characteristics such as data type, outlier type and outlier degree.