The Wireless Sensor Networks (WSNs) used for the monitoring applications like pipelines carrying oil, water, and gas; perimeter surveillance; border monitoring; and subway tunnel monitoring form linear WSNs. Here, the infrastructure being monitored inherently forms linearity (straight line through the placement of sensor nodes). Therefore, such WSNs are called linear WSNs. These applications are security critical because the data being communicated can be used for malicious purposes. The contemporary research of WSNs data security cannot fit in directly to linear WSN as only by capturing few nodes, the adversary can disrupt the entire service of linear WSN. Therefore, we propose a data aggregation scheme that takes care of privacy, confidentiality, and integrity of data. In addition, the scheme is resilient against node capture attack and collusion attacks. There are several schemes detecting the malicious nodes. However, the proposed scheme also provides an identification of malicious nodes with lesser key storage requirements. Moreover, we provide an analysis of communication cost regarding the number of messages being communicated. To the best of our knowledge, the proposed data aggregation scheme is the first lightweight scheme that achieves privacy and verification of data, resistance against node capture and collusion attacks, and malicious node identification in linear WSNs.

用于监测应用的无线传感器网络 (WSN)，如输送石油、水和天然气的管道；周界监视；边境监测；和地铁隧道监测形成线性 WSN。在这里，被监控的基础设施固有地形成线性（通过传感器节点放置的直线）。因此，这种 WSN 被称为线性 WSN。这些应用程序对安全至关重要，因为正在通信的数据可用于恶意目的。当代对 WSN 数据安全性的研究不能直接适用于线性 WSN，因为攻击者仅通过捕获少数节点就可以破坏线性 WSN 的整个服务。因此，我们提出了一种数据聚合方案，可以照顾到数据的隐私、机密性和完整性。此外，该方案对节点捕获攻击和共谋攻击具有弹性。有几种检测恶意节点的方案。然而，所提出的方案还提供了对密钥存储要求较低的恶意节点的识别。此外，我们还提供了有关通信消息数量的通信成本分析。据我们所知，所提出的数据聚合方案是第一个实现数据隐私和验证、抵抗节点捕获和共谋攻击以及线性 WSN 中的恶意节点识别的轻量级方案。我们提供了一个关于通信消息数量的通信成本分析。据我们所知，所提出的数据聚合方案是第一个实现数据隐私和验证、抵抗节点捕获和共谋攻击以及线性 WSN 中的恶意节点识别的轻量级方案。我们提供了一个关于通信消息数量的通信成本分析。据我们所知，所提出的数据聚合方案是第一个实现数据隐私和验证、抵抗节点捕获和共谋攻击以及线性 WSN 中的恶意节点识别的轻量级方案。