DHA-Net enabled key generation and Trust based authentication framework for Edge-cloud IoT System

Purpose:Securing an IoT-Edge-Cloud Because of inadequate power distribution, the environment presents serious issues. The scattered nature of devices, and a lack of standardization. This research proposes a novel framework integrating Deep High-order Attention Neural Network (DHA-Net) enabled key generation and Trust-based Authentication to address these challenges. The methodology comprises seven key steps: initialization, registration, key generation, data access control, trust-based authentication, authorization, and data protection. Strong authentication procedures and secure communication are guaranteed by the suggested framework. Initialization allows devices to join the network securely, while registration establishes trust for new devices. Keys for security are generated for encryption and decryption procedures using DHA-Net-powered key creation. Data access control makes guarantee that sensitive resources can only be accessed by authorized individuals or devices. Trust-based authentication evaluates device or user identity using various types of trust, identity, attestation, and mediation trust, moving beyond traditional credential-based systems. Security operations such as DES encryption, hashing functions, OTPs, and XOR functions are employed to strengthen the system's resilience. The framework's performance is evaluated using metrics like authorization time, privacy rate, and memory consumption. Python tools are used to implement the DHA-Net-based framework. The proposed approach enhances security in IoT systems, ensuring data confidentiality, integrity, and reliable authentication.

Keywords - IoT Security, DHA-Net, Trust-Based Authentication, Key Generation, Edge-Cloud Computing, Data Access Control.