BIO-INSPIRED BASED SEGMENTATION AND USER AUTHENTICATED KEY MANAGEMENT FOR IOT NETWORKS

Abstract

Data exchanging and gathering is greatly achieved by several interconnected physical objects or smart devices over the Internet are termed as Internet of Things (IoT). A generic IoT network called Hierarchical IoT Network (HIoTN) inclusive of the organized different nodes in a hierarchy as gateway node, cluster head nodes and sensing nodes. In HIoTN of generic IoT networking environment for a particular application, user direct access in real-time data from the sensing nodes is necessitated. Recent work introduces a User Authenticated Biometric Key Management Protocol (UABKMP) for IoT network. Hence this proposed work exhibits new region of interest based segmentation algorithm with base procedure of Modified Bat optimization (MBO) algorithm hybrid with Active Contour Model. In the MBO algorithm the parameters of the bat is tuned via the use of the Brownian Distribution. Finally an Authenticated Key Management (AKM) is proposed for IoT network. The Real-Or-Random (ROR) model is incorporated in network for proving the scheme formal security and also ensures the informal security being protected from several probable attacks.

Keywords

• hierarchical iot network
• authentication
• key management
• security
• segmentation
• modified bat optimization
• active contour model