A Recent Systematic Review of Cloud-Assisted Web Filtering Framework using Software-Defined Networking

Lukmanulhakim Ngah; Mohd Nordin Abdul Rahman

Lukmanulhakim Ngah University College TATI
Mohd Nordin Abdul Rahman UNISZA

Keywords: SDN, Cloud Computing, Web-Filtering

Abstract

The increasing complexity of cloud and network environments has intensified the need for more advanced web filtering mechanisms, particularly those leveraging Software-Defined Networking (SDN). This systematic literature review examines the current state of research on "Cloud-Assisted Web Filtering Framework using SDN" to address existing gaps and emerging challenges. The problem lies in the evolving security threats, resource management inefficiencies, and scalability limitations faced by traditional network architectures. To systematically explore these issues, the PRISMA protocol was applied, with data collection conducted across two leading scientific databases, Web of Science and Scopus. A total of 24 primary studies were identified and analysed. The findings were organized into three thematic categories: (1) Security and Attack Mitigation in SDN and IoT Systems, where advanced frameworks for intrusion detection and DDoS mitigation were prominent; (2) Intelligent Resource Management and Optimization in SDN, Fog, and Edge Systems, focusing on strategies such as reinforcement learning and blockchain-based task offloading to enhance resource utilization; and (3) Network Management, Scalability, and Architectural Innovations, highlighting developments in hierarchical control models, federated authentication systems, and SD-WAN traffic prediction. The results demonstrate significant advancements in applying SDN to support more adaptive, resilient, and efficient cloud-assisted web filtering solutions. However, challenges remain, particularly concerning integration complexity, latency management, and ensuring robust multi-domain coordination. In conclusion, this review provides a comprehensive synthesis of current approaches and identifies critical areas for future research, emphasizing the importance of intelligent, secure, and scalable frameworks in the evolving landscape of cloud and SDN-based web filtering systems.