Smart Contracts and Anomaly Detection in SDN environment using Cloud-Edge Integration Model

Abstract

Software Defined Network (SDN) has permitted revolutionary networking solutions by the separation of manage and statistics planes and the centralization of network administration. Nevertheless, SDN networks without robust get right of access to manage may be prone to protection breaches and unapproved gain admission to, consequently giving significant hazards. Rapid and accurate anomaly detection and access control are important in cloud-aspect collaborative networks, given to the fact permitted devices have the opportunity to turn malevolent. We suggest the exploitation of a modern cloud-primarily based collaboration network architecture that makes use of SDN and neural networks to solve these challenging circumstances. Attribute-Based Access management (ABAC) and smart contracts give accurate community device access management in our machine. In addition, we present a totally new approach for identifying anomalies in Cloud-Edge Collaborative (KPI) data with the assistance of the employment of an effective aggregate of GRU-GAN. This hybrid technique finds prevalent devices, enabling preemptive discount of dangers. This response moreover employs blockchain era to beautify protection. The decentralised and tamper-evident structure of blockchain promotes obtain right of entry to manage and ensures the integrity of community transactions. Experimental effects argue that our method discovers irregularities greater across datasets. Network integrity is secured by the implementation of popularity-based get right of access to rules, which minimise malicious tool assaults. This full strategy blends SDN, neural networks, and blockchain generation to defend cloud-location collaboration networks against unapproved get right of access to and criminal hobby. This specialised technique secures network assets and creates the basis for current day-day community infrastructures to be lasting and truthful.