SDN-enabled adaptive security framework for multi-cloud infrastructures using deep learning-based threat detection and policy management
Abstract
Organizations achieve agility, expandability, and enhanced resource utilization in multi-cloud environments but encounter notable challenges in ensuring uniform and strong security across varied cloud platforms. The diversity of cloud providers, each with distinct configurations and security policies, complicates harmonized policy enforcement, creating significant vulnerabilities in data protection and threat detection. Moreover, the shifting and dispersed nature of multi-cloud operations broaden the attack surface, rendering real-time threat mitigation more complex. To address these challenges, we introduced a groundbreaking Software-Defined Networking (SDN)-enabled framework incorporating deep learning for attack detection and adaptive security policy management. The developed framework consists of two primary components: Software Defined Multicloud Defense Controller (SDMDC), which delivers centralized, instantaneous security policy enforcement (control plane), while MCIDS-G facilitates widespread threat detection across cloud platforms (Data plane). SDMDC’s comprehensive IDS system was constructed using the Cross-Cloud Threat Transformer model. MCIDS-G’s regional IDS system was formulated using the LSTM model.
Additionally, the Lemerus optimizer is utilized in SDMDC for economic policy management. SDMDC implements security standards that extend all cloud environments where applications operate. Cloud security issues persist because the solution integrates coordinated international security techniques with threat identification abilities and policy administration systems. The SDMDC manage the input and output of traffic and east-west movement between separate cloud environments, including AWS and supplementary service providers. Fundamental scalability capabilities function with flexible functions in the proposed framework. The system provides automatic policy implementation between platforms and facilitates instantaneous reaction to threats to preserve security consistency. Our finalized developments have revolutionized this work through a crucial breakthrough. The proposed framework signifies an improved security solution compared to existing multi-cloud protection approaches, which introduces new research directions. Research advancement in new directions becomes feasible when traffic management elements, firewall integrations and FQDN policy enforcement with proxy management solutions are deployed.