DDoS Attack Monitoring using Smart Controller Placement in Software Defined Networking Architecture

Haque, Muhammad Reazul; Tan, Saw Chin; Yusoff, Z.; Lee, Ching K.; Kaspin, Rizaludin

doi:10.1007/978-981-13-2622-6_20

Cited by 15 publications

(14 citation statements)

References 12 publications

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“…Author uses TCFI module for traffic collection and feature extraction from traffic flow however, it is difficult to when it comes to detection of low rate attacks from the proffered technique as it alike the regular/genuine traffic from victim end. Reference [35] presents a hypothetical main smart controller placement over other controllers in SDNs for continuous service. However, extra controllers placement will surely slow the SDN network as it is one of the main challenges that SDN networks are facing especially at enterprise level, will rise the scalability issues in SDN environment as well.…”

Section: Related Workmentioning

confidence: 99%

A Deep CNN Ensemble Framework for Efficient DDoS Attack Detection in Software Defined Networks

et al. 2020

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As novel technologies continue to reshape the digital era, cyberattacks are also increasingly becoming more commonplace and sophisticated. Distributed denial of service (DDoS) attacks are, perhaps, the most prevalent and exponentially-growing attack, targeting the varied and emerging computational network infrastructures across the globe. This necessitates the design of an efficient and early detection of large-scale sophisticated DDoS attacks. Software defined networks (SDN) point to a promising solution, as a network paradigm which decouples the centralized control intelligence from the forwarding logic. In this work, a deep convolutional neural network (CNN) ensemble framework for efficient DDoS attack detection in SDNs is proposed. The proposed framework is evaluated on a current state-of-the-art Flow-based dataset under established benchmarks. Improved accuracy is demonstrated against existing related detection approaches. INDEX TERMS Software defined network (SDN), anomaly detection, distributed denial of service (DDoS), deep learning, deep convolutional neural network (CNN).

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Section: Related Workmentioning

confidence: 99%

A Deep CNN Ensemble Framework for Efficient DDoS Attack Detection in Software Defined Networks

et al. 2020

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“…The heuristic algorithm adequately unravels the CPP by applying the advanced boundaries acquired in the POM, but the authors present no mechanism to protect the SDN primary controller and infrastructure. Another proposal used a hypothetical concept of smart controller placement for SDNs [46]. The use of SDNs is expanding, being used in applications such as voice over IP (VoIP) [47][48][49], fiber optic networks [50][51][52], worldwide interoperability for microwave access (WiMAX) networks [53][54][55], multiple input multiple output (MIMO) [56], Named Data Networking (NDN) [57][58][59] and cloud computing network [60], artificial intelligence (AI) and machine learning [ML] networks [61], and unmanned aerial vehicle (UAV) and autonomous electric vehicle (AEV) control through satellite networks [62].…”

Section: Related Workmentioning

confidence: 99%

Automated Controller Placement for Software-Defined Networks to Resist DDoS Attacks

Haque¹,

Tan²,

Yusoff³

et al. 2021

Computers, Materials &Amp; Continua

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“…The author in [58] discussed SDN specific centralization creates scalability problems in large network environments. [59] proposed a hypothetical concept of smart controller placement for SDN architecture. [60] Studied the SDN controller circumstance issue for single-interface and multiassociate frustrations, exclusively.…”

Section: Related Workmentioning

confidence: 99%

A Novel DDoS Attack-aware Smart Backup Controller Placement in SDN Design

Haque¹,

Tan²,

Yusoff³

et al. 2020

AETiC

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Security issues like Distributed Denial of Service (DDoS) attacks are becoming the main threat for Software-Defined Networking (SDN). Controller placement is a fundamental factor in the design and planning of SDN infrastructure. The controller could be seen as a single dot of failure for the whole SDN and it's the alluring point for DDoS attack. Single controller placement implies a single point of SDN control. So, there is a very high chance to fail the entire network topology as the controller associated with all switches. As a result, legitimate clients won't have the capacity to use SDN services. This is the reason why the controller is the suitable center dot of attack for the aggressor. To protect SDN from this type of single purpose of failure, it is essential to place multiple smart backup controllers to guarantee the SDN operation. In this paper, we propose a novel Integer Linear Programming (ILP) model to optimize the security issue by placing powerful smart backup controller. Result obtained from the simulation shows that our proposed novel ILP model can suggest single or multiple smart backup controller placement to support several ordinary victim controllers which has the capacity to save the cost of multiple ordinary controllers by sharing link, maximum new flows per second of controller and port, etc.

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DDoS Attack Monitoring using Smart Controller Placement in Software Defined Networking Architecture

Cited by 15 publications

References 12 publications

A Deep CNN Ensemble Framework for Efficient DDoS Attack Detection in Software Defined Networks

A Deep CNN Ensemble Framework for Efficient DDoS Attack Detection in Software Defined Networks

Automated Controller Placement for Software-Defined Networks to Resist DDoS Attacks

A Novel DDoS Attack-aware Smart Backup Controller Placement in SDN Design

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