DARE: evaluating Data Accuracy using node REputation

Abstract Typical wireless sensor networks (WSNs) applications are characterized by a certain number of different requirements such as: data accuracy, localization, reputation, security, and confidentiality. Moreover, being often battery powered, WSNs face the challenge of ensuring privacy and security despite power consumption limitations. When the application scenario allows their use, data aggregation techniques can significantly reduce the amount of data exchanged over the wireless link at the price of an increased computational complexity and the potential exposition to data integrity risks in the presence of malicious nodes. In this paper, we propose DARE, an hybrid architecture combining WSNs with the wireless mesh networking paradigm in order to provide secure data aggregation and node reputation in WSNs. Finally, the use of a secure verifiable multilateration technique allows the network to retain the trustworthiness of aggregated data even in the presence of malicious node. Extensive performance evaluations carried out using simulations as well as a real-world prototype implementation, show that DARE can effectively reduce the amount of data exchanged over the wireless medium delivering up to 50% battery lifetime improvement to the wireless sensors.