Routing-Aware and Malicious Node Detection in a Concealed Data Aggregation for WSNs

Abstract

Data aggregation in Wireless Sensor Networks (WSNs) can effectively reduce communication overheads and reduce the energy consumption of sensor nodes. A WSN needs to be not only energy efficient but also secure. Various attacks may make data aggregation unsecure. We investigate the reliable and secure end-to-end data aggregation problem considering selective forwarding attacks and modification attacks in homogeneous WSNs, and propose two data aggregation approaches. Our approaches, namely Sign-Share and Sham-Share, use secret sharing and signatures to allow aggregators to aggregate the data without understanding the contents of messages and the base station to verify the aggregated data and retrieve the raw data from the aggregated data. To the best of our knowledge, this is the first lightweight en-routing malicious node detection in concealed data aggregation. We have performed an extensive simulation to compare our approaches and the two state-of-the-art approaches PIP and RCDA-HOMO. The simulation results show that both Sign-Share and Sham-Share consume a reasonable amount of time in processing and aggregating the data. The simulation results show that our first approach achieved an average network lifetime of 102.33% over PIP and average aggregation energy consumption of 74.93%. In addition, it achieved an average aggregation processing time and sensor data processing time of 95.4% and 90.34% over PIP and 98.7% and 92.07% over RCDA-HOMO, respectively, and it achieved an average network delay of 71.95% over PIP. Although RCDA-HOMO is completely a different technique, a comparison was performed to measure the computational overhead.