Sustainable Network by Enhancing Attribute-Based Selection Mechanism Using Lagrange Interpolation

Abstract

The security framework in Ad-hoc Networks (ANET) continues to attract the attention of researchers, although significant work has been accomplished already. Researchers in the last couple of years have shown quite an improvement in Identity Dependent Cryptography (IDC). Security in ANET is hard to attain due to the vulnerability of links (Wireless). IDC encompasses Polynomial Interpolations (PI) such as Lagrange, curve-fitting, and spline to provide security by implementing Integrated Key Management (IKM). The PI structure trusts all the available nodes in the network and randomly picks nodes for the security key generation. This paper presents a solution to the trust issues raised in Lagrange’s-PI (LI) utilizing an artificial neural network and attribute-based tree structure. The proposed structure not only improves the trust factor but also enhances the accuracy measures of LI to provide a sustainable network system. Throughput, PDR, noise, and latency have been increased by 47%, 50%, 34%, and 30%, respectively, by using LI and incorporating the aforementioned techniques.