ANDES: an Anomaly Detection System for Wireless Sensor Networks

In this paper, we propose ANDES, a framework for detecting and finding the root causes of anomalies in operational wireless sensor networks (WSNs). The key novelty of ANDES is that it correlates information from two sources: one in the data plane as a result of regular data collection in WSNs, the other in the management plane implemented via a separate routing protocol, making it resilient to routing anomaly in the data plane. Evaluation using a 32-node sensor testbed shows that ANDES is effective in detecting fail-stop failures and most routing anomalies with negligible computing and storage overhead.