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Security-aware authorization and verification based data aggregation model for wireless sensor networks

机译：无线传感器网络的安全感知授权和验证基于数据聚合模型

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摘要

In Wireless Sensor Network (WSN), the sensor nodes aggregate the environment and transmit the aggregated data to the Cluster Head (CH) or aggregator. Even though various data aggregation model is introduced, the resource-constrained issues in WSN are complex to solve in the research community. Therefore, the authorization and verification-based data aggregation model is proposed in this research to perform the secure data transmission. The proposed network model contains three functioning blocks, such as sensor nodes, aggregators, and data centers, respectively. The proposed data aggregation model involves five different phases, setup and key generation phase, signing, verification, authorization, and data aggregation phase. The sensor node creates the ID and private key to perform the data communication between the Cluster Head and data center. The data center generates the control message and transfers the message to CH and the sensor node. Finally, the data aggregation is carried out using the trimodel Least Mean Square (LMS) filter to achieve the data aggregation in WSN. Moreover, the proposed authorization and verification-based data aggregation model obtained a lower prediction error of 0.0526 and consumed higher energy of 0.5567 J with the computational and the communication cost as 0.008 second, and 0.0139 second, respectively.
机译：在无线传感器网络（WSN）中，传感器节点聚合环境并将聚合数据发送到群集头（CH）或聚合器。尽管介绍了各种数据聚合模型，但WSN中的资源受限问题是在研究界中解决的复杂性。因此，在该研究中提出了基于授权和验证的数据聚合模型，以执行安全数据传输。所提出的网络模型分别包含三个功能块，例如传感器节点，聚合器和数据中心。所提出的数据聚合模型涉及五个不同的阶段，设置和键生成阶段，签名，验证，授权和数据聚合阶段。传感器节点创建ID和私钥以执行群集头和数据中心之间的数据通信。数据中心生成控制消息并将消息传输到CH和传感器节点。最后，使用Trimodel最小均方（LMS）滤波器执行数据聚合以实现WSN中的数据聚合。此外，所提出的授权和基于验证的数据聚合模型获得了0.0526的较低预测误差，并将0.5567倍的较高能量为0.008秒和0.0139秒分别为0.008秒和0.0139秒。

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