Stream-Based Authentication Strategy Using IoT Sensor Data in Multi-homing Sub-aqueous Big Data Network

Big data analytics has addressed many in-place and remote network issues in a sub-aqueous distributed computing environment. Recently, a new phenomenon is introduced in the data analytics clusters that focus on multi-homing network connectivity procedures among off-ground multiple nodes of the large-scale on-running wireless industrial applications. In this way, the clusters perform multi-layer cross-connected task processing among various networks simultaneously and perform stream based data block placement over multiple nodes in a sequential order. This satisfies the procedural performance of the cluster; however, security remains an open issue in it because of unavailability of inter-network data block processing authorization. In this paper, we propose a stream based authentication mechanism, that specifically addresses security concerns of multi-homing sub-aqueous big data networks and presents a key authorization infrastructure that performs a proper handing taking among multiple off-ground Datanodes before an inter-network data block exchange. The simulation results depict that our approach increases multi-homing network compatibility and reliability while processing a data block in the sub-aqueous distributed computing environment.