Stateful firewall‐enabled software‐defined network with distributed controllers: A network performance study

Prabakaran, Senthil; Ramalakshmi, R.

doi:10.1002/dac.4237

Cited by 10 publications

(3 citation statements)

References 27 publications

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“…Experimental results on the Ryu driver and the Mininet emulator show poor overall performance on modern hardware. Şeyma Aymaz et al [11] This paper developed into a new generation of networking that separates processing and recording planes, enables network scheduling, and responds fast to converting conditions via imparting a global view of the network. To triumph over the restrictions of previous community infrastructure, The SDN sits for load balancing above the coping with level.…”

Section: Genetu Y Basena Et Al [9]mentioning

confidence: 99%

Dynamic Weighted Round Robin Approach in Software-Defined Networks Using Pox Controller

Manasa¹,

Babu²

2023

IJRITCC

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Load balancing is important in solving over-load traffic problems in the network. Therefore, it has been among the first appealing applications in Software Defined Networking (SDN) networks. Numerous SDN-based load-balancing approaches have been recommended to enhance the performance of SDN networks. However, network control could be more manageable in large networks with hundreds of switches and routers. The SDN is a unique way of building, controlling, and developing networks to modify this unpleasant situation. The major concept of SDN contains logically centralizing network management in an SDN controller, which manages and observes the behaviour of the network. Numerous load-balancing approaches are known, such as Round Robin (RR), random policy, Weighted randomized policy (WRP), etc. Every load-balancing policy approach has some benefits and detriments. This paper developed an advanced load-balancing algorithm, a dynamic weighted round-robin (DWRR), and ran it on the top of the SDN controller. Then we calculate the result of our proposed load-balancing approach by comparing it with the current round-robin (RR) and weighted round-robin (WRR) approaches. Mininet tool is utilized for the investigation, and the controller utilized as the control plane is named the POX controller.

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Section: Genetu Y Basena Et Al [9]mentioning

confidence: 99%

Dynamic Weighted Round Robin Approach in Software-Defined Networks Using Pox Controller

Manasa¹,

Babu²

2023

IJRITCC

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“…Four distinct algorithms are used: BayesNet, Naive-Bayes, C4.5, DT, and [ 61 ] to predict the victim being targeted and to evaluate their accuracy results. A stateful firewall is deployed in distributed SDN controllers, where the OpenFlow protocol is used by the controllers and switches to send and receive control messages [ 62 , 63 , 64 ]. IP aliases are created on Stateful Firewall VNF and are updated based on machine learning threat detection algorithms.…”

Section: Proposed Workmentioning

confidence: 99%

Predicting Attack Pattern via Machine Learning by Exploiting Stateful Firewall as Virtual Network Function in an SDN Network

Prabakaran

Ramalakshmi

Hussain

et al. 2022

Sensors

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Decoupled data and control planes in Software Defined Networks (SDN) allow them to handle an increasing number of threats by limiting harmful network links at the switching stage. As storage, high-end servers, and network devices, Network Function Virtualization (NFV) is designed to replace purpose-built network elements with VNFs (Virtualized Network Functions). A Software Defined Network Function Virtualization (SDNFV) network is designed in this paper to boost network performance. Stateful firewall services are deployed as VNFs in the SDN network in this article to offer security and boost network scalability. The SDN controller’s role is to develop a set of guidelines and rules to avoid hazardous network connectivity. Intruder assaults that employ numerous socket addresses cannot be adequately protected by these strategies. Machine learning algorithms are trained using traditional network threat intelligence data to identify potentially malicious linkages and probable attack targets. Based on conventional network data (DT), Bayesian Network (BayesNet), Naive-Bayes, C4.5, and Decision Table (DT) algorithms are used to predict the target host that will be attacked. The experimental results shows that the Bayesian Network algorithm achieved an average prediction accuracy of 92.87%, Native–Bayes Algorithm achieved an average prediction accuracy of 87.81%, C4.5 Algorithm achieved an average prediction accuracy of 84.92%, and the Decision Tree algorithm achieved an average prediction accuracy of 83.18%. There were 451 k login attempts from 178 different countries, with over 70 k source IP addresses and 40 k source port addresses recorded in a large dataset from nine honeypot servers.

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“…Once network states are modified, FlowGuard examines network flow path fields to identify firewall protocol breaches and implements automated real-time breach solutions [17]. Using the Ostinato traffic generator tool, traffic size ranging from 64 bytes to 8950 bytes is created which is capable of achieving a maximum bandwidth of 9 Gbps [18]. Three major issues in network administration are allowing rapid updates in network status, ensuring assistance in a high-level language for network setup, and offering improved access and control over functions for network monitoring and configuring [19].…”

Section: Literature Workmentioning

confidence: 99%

Performance Evaluation of Stateful Firewall-Enabled SDN with Flow-Based Scheduling for Distributed Controllers

et al. 2022

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Software-defined networking (SDN) is a network approach achieved by decoupling of the control and data planes. The control plane is logically centralized and the data plane is distributed across the network elements. The real-time network is in need of the incorporation of distributed controllers to maintain distributed state information of the traffic flows. Software-based solutions aid distributed SDN controllers to handle fluctuating network traffic and the controller’s configurations are dynamically programmed in real time. In this study, SDN controllers were programmed with a stateful firewall application to provide firewall functionalities without the support of committed hardware. A stateful firewall filtered traffic based on the complete context of incoming packets; it continuously evaluated the entire context of traffic flows, looking for network entry rather than specific traffic flows. In addition, a flow-based scheduling module was implemented in the distributed controllers to improve network scalability. A network cluster was configured with three distributed controllers and we experimented with three independent network topologies. The performance of the proposed network model was evaluated by measuring and analyzing metrics such as network throughput (kbps), delay (ms) and network overhead (pkt/ms) for various combinations of controllers and topologies. The results of the analysis were determined using the mininet emulator. The findings of the performance evaluation indicate that the distributed SDN controllers performs better than a centralized controller. When comparing distributed SDN with two controllers and distributed SDN with three controllers the overall network throughput is increased by 64%, the delay is decreased by 43% and network overhead is reduced by 39%.

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Stateful firewall‐enabled software‐defined network with distributed controllers: A network performance study

Cited by 10 publications

References 27 publications

Dynamic Weighted Round Robin Approach in Software-Defined Networks Using Pox Controller

Dynamic Weighted Round Robin Approach in Software-Defined Networks Using Pox Controller

Predicting Attack Pattern via Machine Learning by Exploiting Stateful Firewall as Virtual Network Function in an SDN Network

Performance Evaluation of Stateful Firewall-Enabled SDN with Flow-Based Scheduling for Distributed Controllers

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