SDN/NFV Enabled Security for an Enterprise Network using Commodity Hardware

Saeed, Rizwan; Qureshi, Safwan; Farooq, Muhammad Umar; Zeeshan, Muhammad

doi:10.1109/iccece55162.2022.9875076

Cited by 2 publications

(3 citation statements)

References 15 publications

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“…This scheme dynamically selects the optimal path for security SFC in real time using the DQN algorithm, considering the features of incoming traffic and the detection results of security service functions. Furthermore, in [11], a SDN/NFV-enabled security solution is proposed for enterprises, leveraging the commodity hardware to reduce both capital and operational expenditures.…”

Section: Related Workmentioning

confidence: 99%

IDSMatch: A Novel Deployment Method for IDS Chains in SDNs

Niknami,

2024

Network

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With the surge in cyber attacks, there is a pressing need for more robust network intrusion detection systems (IDSs). These IDSs perform at their best when they can monitor all the traffic coursing through the network, especially within a software-defined network (SDN). In an SDN configuration, the control plane and data plane operate independently, facilitating dynamic control over network flows. Typically, an IDS application resides in the control plane, or a centrally located network IDS transmits security reports to the controller. However, the controller, equipped with various control applications, may encounter challenges when analyzing substantial data, especially in the face of high traffic volumes. To enhance the processing power, detection rates, and alleviate the controller’s burden, deploying multiple instances of IDS across the data plane is recommended. While deploying IDS on individual switches within the data plane undoubtedly enhances detection rates, the associated costs of installing one at each switch raise concerns. To address this challenge, this paper proposes the deployment of IDS chains across the data plane to boost detection rates while preventing controller overload. The controller directs incoming traffic through alternative paths, incorporating IDS chains; however, potential delays from retransmitting traffic through an IDS chain could extend the journey to the destination. To address these delays and optimize flow distribution, our study proposes a method to balance flow assignments to specific IDS chains with minimal delay. Our approach is validated through comprehensive testing and evaluation using a test bed and trace-based simulation, demonstrating its effectiveness in reducing delays and hop counts across various traffic scenarios.

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Section: Related Workmentioning

confidence: 99%

IDSMatch: A Novel Deployment Method for IDS Chains in SDNs

Niknami,

2024

Network

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“…The rise of digital networks has increased cyber threats, and protecting these networks has become more challenging than ever 1 . Software‐defined networking (SDN) is a new paradigm that offers several benefits over traditional networking, including centralized control, improved flexibility, programmability, and increased scalability 2 . In addition, SDN provides an ideal platform for implementing advanced security mechanisms, such as anomaly detection, to protect against evolving cyber threats 3 …”

Section: Introductionmentioning

confidence: 99%

“…1 Software-defined networking (SDN) is a new paradigm that offers several benefits over traditional networking, including centralized control, improved flexibility, programmability, and increased scalability. 2 In addition, SDN provides an ideal platform for implementing advanced security mechanisms, such as anomaly detection, to protect against evolving cyber threats. 3 Anomaly detection is a critical aspect of network security.…”

Section: Introductionmentioning

confidence: 99%

Unleashing the power of SDN and GNN for network anomaly detection: State‐of‐the‐art, challenges, and future directions

Dhadhania,

Bhatia,

Mehta

et al. 2023

Security and Privacy

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Modern computer networks' increasing complexity and scale need serious attention towards network anomaly detection. Software‐defined networking (SDN) and graph neural networks (GNN) have emerged as promising approaches for anomaly detection due to their ability to capture dynamic network behavior and learn complex patterns from large‐scale network data. The amalgamation of SDN and GNN for network anomaly detection presents promising opportunities for improving the accuracy and efficiency of network anomaly detection. This paper focuses on various trends, issues, and challenges by integrating GNN on the top of SDN for network anomaly detection. The article highlights the advantages of using SDN for providing fine‐grained control and programmability in network monitoring. At the same time, GNN can model network behavior as a graph and learn representations from graph‐structured data. The authors also discuss the limitations of traditional anomaly detection methods in SDN, such as rule‐based approaches, and the potential of GNN to overcome these limitations by leveraging their ability to capture non‐linear and dynamic patterns in network data. This paper also presents a case study of DoS attack detection using SDN. The result shows that SDN based approach helps to detect attacks with an accuracy of 97% with future research directions.

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SDN/NFV Enabled Security for an Enterprise Network using Commodity Hardware

Cited by 2 publications

References 15 publications

IDSMatch: A Novel Deployment Method for IDS Chains in SDNs

IDSMatch: A Novel Deployment Method for IDS Chains in SDNs

Unleashing the power of SDN and GNN for network anomaly detection: State‐of‐the‐art, challenges, and future directions

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