A condition-based distributed approach for secured privacy preservation of nodes in wireless sensor networks IoT

The fast expansion of wireless sensor network-internet of things (WSN-IoT) in recent years has led to the adoption of a vital infrastructure. Adversaries who work together to carry out privacy-related attacks and capture sensitive information from critical infrastructure for a range of personal, political, and commercial purposes, thus security and node preserving have been one of the key areas of research in WSN-IoT. Existing security and privacy research work focuses on cryptography, either which is less efficient, or it majorly focuses on securing the network, which further leads to exposing the nodes to the vulnerability in terms of privacy in the network. This research develops condition-based distributed privacy-preserving (CDPP) approach to preserve the sensor node privacy; the CDPP algorithm develops a condition based on which the nodes' vulnerable information is preserved and not accessed by the compromised nodes. CDPP architecture is evaluated considering the amount of misclassified nodes for safeguarding the node in the network. CDPP is evaluated by inducing the corrupt nodes and further comparing the model with existing low energy adaptive clustering hierarchy (LEACH) based on classification, misclassification and throughput. Furthermore, comparative analysis proves the marginal improvisation in terms of discussed parameter against existing protocol.