Fuzzy integrated Bayesian Dempster–Shafer theory to defend cross-layer heterogeneity attacks in communication network of Smart Grid

Abstract

Cross-layer heterogeneity is a critical issue in designing a secured communication network for a Smart Grid, as it shows a high degree of uncertainty during packet transmission. In this paper, the Bayesian theory is combined with Dempster–Shafer theory (BDST) to handle physical layer (transmission rate of the node) and medium access control (MAC) layer (buffering capacity of the node) metrics to calculate trust at node level for packet delivery. Further, the fuzzy theory is integrated with BDST to handle MAC layer (Capacity of the link) and Network layer (Distance and Link Quality) metrics for calculating trust at link level for secured routing. Experimental setup is created using Network Simulator 2 (NS2) to demonstrate how the cross-layer metrics are handled by the proposed fuzzy-based Bayesian Dempster–Shafer trusted routing (BDSFTR). Extensive experiments are conducted with the inclusion of malicious and faulty nodes to highlight the performances of the proposed BDSFTR in the identification of the on-off, packet dropping, and bad-mouthing attacks. From the simulation results, it is clear that the proposed model provides a reliable and secured trust-based routing framework for the communication network of smart grid.