Trustworthy and protected data collection for event detection using networked sensing systems
Md Zakirul Alam Bhuiyan, Jie Wu · 2016
Data collection in wireless networked sensing systems (WNSS) is usually not reliable due to sensor faults and/or security attacks. This makes detection of an event (e.g., structural damage) through data aggregation unreliable. In this paper, we propose a trustworthy and protected data collection (TPDC) framework for event detection in WNSS. This framework facilitates reliable data for aggregation at clusters of WNSS. The key idea of TPDC is to allow a cluster head to check whether or not the transmitted data is trustworthy (i.e., unaltered estimated at the sensor node level) and protected (i.e., received without alteration after the transmission) before aggregating the data at a cluster. For the trustworthy data, we propose an algorithm to make sure that transmitted data is unaltered. For the protected data, we present a truth discovery approach, whose goal is to infer truthful facts from unreliable sensor data. Through simulations, we demonstrate that the collected data in TPDC is trustworthy and protected that can make aggregation for event detection reliable.