Outlier Detection Using Support Vector Machine in Wireless Sensor Network Real Time Data
Outlier detection has many important applications in sensor networks, e.g., abnormal event detection, animal behavior change, intruder detection etc. Outliers in Wireless Sensor Networks (WSNs) are sensor nodes that issue attacks by abnormal behaviours and fake message broadcasting. The probable sources of outliers include noise and errors, events, and malicious attacks on the network. Wireless Sensor Networks (WSNs) are more likely to generate outliers due to their special characteristics, e.g. constrained available resources, frequent physical failure, and often harsh deployment area. In this paper, the authors motivate their technique in the context of the problem of outlier detection. This paper is going to present the real time network outlier detection method in the wireless sensor networks.