Secure data collection in wireless sensor networks

Wireless sensor networks (WSNs) are used to collect various data in environment monitoring applications. The most comprehensive way of data collection is to make every sensor node report periodically its sensing data to a base node. To reduce the energy consumption due to excessive communication, the network is partitioned into a set of spatial clusters with similar sensing data. For each cluster, only a few sensor nodes (samplers) report their sensing data to the base node. The base node may predict the missed data of non-samplers using the spatial correlation between sensor nodes. The spatial clustering is vulnerable to internal security threat such as node compromise. If the samplers are compromised and report incorrect data intentionally, then the WSN should be contaminated rapidly due to the process of data prediction at the base node. In this paper, we propose intrusion detection algorithms for secure data collection in the WSN. The algorithms consist of cluster head monitoring and member node monitoring to cope with security attacks where either a cluster head or member nodes are compromised.