Privacy-aware secured discrete framework in wireless sensor network

Rapid expansion of wireless sensor network-internet of things (WSN-IoT) in
terms of application and technologies has led to wide research considering
efficiency and security aspects. Considering the efficiency approach such as
data aggregation along with consensus mechanism has been one of the
efficient and secure approaches, however, privacy has been one of major
concern and it remains an open issue due to low classification and high
misclassification rate. This research work presents the privacy and reliable
aware discrete (PRD-aggregation) framework to protect and secure the
privacy of the node. It works by initializing the particular variable for each
node and defining the threshold; further nodes update their state through the
functions, and later consensus is developed among the sensor nodes, which
further updates. The novelty of PRD is discretized transmission for
efficiency and security. PRD-aggregation offers reliability through efficient
termination criteria and avoidance of transmission failure. PRD-aggregation
framework is evaluated considering the number of deceptive nodes for
securing the node in the network. Furthermore, comparative analysis proves
the marginal improvisation in terms of discussed parameter against the
existing protocol.