Hybrid Compressed Sensing and Secure Fault Tolerant Data Aggregation in Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSNs) commonly comprise numerous low-cost sensor nodes that possess limited sensing, computation, and communication capabilities. Given the constrained resources of these sensor nodes, it becomes crucial to minimize data transmission to enhance both the average sensor lifetime and overall bandwidth utilization. Data aggregation serves as a process of summarizing and merging sensor data to reduce the volume of data transmitted within the network. Since wireless sensor networks are typically deployed in remote and challenging environments for transmitting sensitive information, sensor nodes are vulnerable to node compromise attacks. Consequently, security issues such as data confidentiality and integrity assume paramount importance. Therefore, when designing wireless sensor network protocols, such as data aggregation protocols, it is imperative to prioritize security and energy efficiency. In this work, we focus on these issues and develop a novel data aggregation approach by using a compressed sensing mechanism. The proposed approach is Hybrid Compressed sensing Secure Fault Tolerant Data Aggregation (HCSFTDA). Moreover, we focus on incorporating security therefore we present a novel mechanism for key distribution and data integrity verification. The performance of the HCSFTDA approach is measured in terms of packet delivery rate, average energy consumption and overhead and compared with existing approaches. The comparative analysis shows that the HCSFTDA achieved better performance. The experimental analysis shows that the proposed model reported average energy consumption as 0.0667, packet delivery as 98% and reduced communication overhead as 400 Kbps.