Network Security in Architectures for Software Defined Networking (SDN)

SDN (Software Defined Networking) is a new network design that separates the control and dataplanes, allowing for better network management and centralized control. This decoupling makes networks more programmable, scalable, and flexible, which is critical for meeting the changing requirements of modern digital environments. Although SDN streamlines network administration, it also adds new security risks, such as the possibility of centralized control failures, expanded attack surfaces, and vulnerability to multiple network attack types. SDN architectures must include network security to mitigate these dangers. This includes setting up automated responses to detect and remove threats, as well as implementing security capabilities like real-time traffic monitoring into the SDN controller. Furthermore, SDN's programmability allows for the dynamic deployment of security policies across the network, increasing the network's ability to respond to emerging threats. A more robust and flexible security posture can be achieved by effectively managing and coordinating security solutions like as intrusion detection systems (IDS), firewalls, and distributed denial of service (DDoS) mitigation with SDN controllers. This paper examines many techniques to incorporate network security into SDN systems, highlighting the benefits of centralized policy enforcement, real-time monitoring, and SDN's agility in implementing security measures. Along with future advances such as the use of AI and machine learning for automated incident response and predictive threat analysis, the challenges and restrictions of safeguarding SDN configurations are discussed. To deal with the rising complexity and sophistication of assaults in SDN-based networks, the study underlines the importance of continuous innovation in security mechanism.

Authors

Publication Details

Journal
NEU Journal for Artificial Intelligence and Internet of Things
Published
2025-03-14
DOI
https://doi.org/10.32955/neuaiit202541960
Citations
1
Primary Topic
Software-Defined Networks and 5G
Type
article
Field-Weighted Citation Impact
1.49
Controls
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article

Network Security in Architectures for Software Defined Networking (SDN)

Chadi Altrjman, Ramiz Salama, Fadi M. Al-Turjman
1 citations
NEU Journal for Artificial Intelligence and Internet of Things
Software-Defined Networks and 5G
1.49
article

Network Security in Architectures for Software Defined Networking (SDN)

Chadi Altrjman, Ramiz Salama, Fadi M. Al-Turjman
article en
1 citations

Abstract

SDN (Software Defined Networking) is a new network design that separates the control and dataplanes, allowing for better network management and centralized control. This decoupling makes networks more programmable, scalable, and flexible, which is critical for meeting the changing requirements of modern digital environments. Although SDN streamlines network administration, it also adds new security risks, such as the possibility of centralized control failures, expanded attack surfaces, and vulnerability to multiple network attack types. SDN architectures must include network security to mitigate these dangers. This includes setting up automated responses to detect and remove threats, as well as implementing security capabilities like real-time traffic monitoring into the SDN controller. Furthermore, SDN's programmability allows for the dynamic deployment of security policies across the network, increasing the network's ability to respond to emerging threats. A more robust and flexible security posture can be achieved by effectively managing and coordinating security solutions like as intrusion detection systems (IDS), firewalls, and distributed denial of service (DDoS) mitigation with SDN controllers. This paper examines many techniques to incorporate network security into SDN systems, highlighting the benefits of centralized policy enforcement, real-time monitoring, and SDN's agility in implementing security measures. Along with future advances such as the use of AI and machine learning for automated incident response and predictive threat analysis, the challenges and restrictions of safeguarding SDN configurations are discussed. To deal with the rising complexity and sophistication of assaults in SDN-based networks, the study underlines the importance of continuous innovation in security mechanism.

NEU Journal for Artificial Intelligence and Internet of ThingsVol. 4(1)
Openalex Percentile: Top 19%
Software-Defined Networks and 5G
1.49
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