Secure Adaptive Cluster based Routing Using Multi Objective-Trust based Hybrid Optimization Algorithm for CPS

Abstract

Cyber physical system (CPS) is an engineered system that integrates the physical world with the cyber world through enhanced computation, communication and control (3C) abilities. But, the CPS's sensors are susceptible to malicious threats due to its dynamic topology and open medium of the network. Therefore, an effective secure adaptive cluster-based routing is required to be developed for improving the security of CPS. In this paper, the multi objective-trust based hybrid optimization algorithm (MO-THOA) is proposed to improve CPS security. The MO-THOA is the combination of trust based flower pollination algorithm (TFPA) and trust based ant colony optimization (TACO). In that, the TFPA is used to select a secure adaptive cluster head (ACH) and TACO is used to identify the secure routing path via ACHs. Therefore, the proposed MO-THOA improved the security against malicious attacks while broadcasting the data. The performance of the MO-THOA is evaluated using packet delivery ratio (PDR), average end to end delay (AEED) and normalized routing overhead (NRO). The existing methods namely grey-wolf updated whale optimization algorithm (GU-WOA), moving centroid based routing protocol (MCRP) and multiobjective ant colony optimization (MOACO) are used to evaluate the MO-THOA method. The PDR of the MO-THOA for 20 nodes is 0.981, it is high when compared to the GU-WOA, MOACO and MCRP.