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.

Software Defined Network (SDN) cut down the monopolies of producing network devices and their applications. It allows the use of an omniscient controller that manages the overall network and promises for simplifying the configuration and management burden of the traditional Internet Protocol (IP) network. The use of hardware load balancer is a critical issue in conventional IP networks that creates many negative impacts such as the cost affordability, features customization, and availability. Also, the existing load balancing algorithm does not consider the flow size generated by the client nodes. Further, flows are not classified based on the threshold value of the dynamic flow size. The paper proposes to compare the performance of two load balancing algorithms such as flow-based load balancing algorithm and traffic pattern-based load balancing algorithm with distributed controllers' architecture. The result shows that the flow-based load balancing algorithm minimizes response time by 94%, enhances transaction rate by 14% and Traffic pattern-based load balancing algorithm has improved availability by 2.69%.

SummarySoftware-defined network (SDN) is constructed by decoupling the control and data plane from the forwarding devices. The control plane operations are managed by centralized or distributed controllers, and the data plane operation is managed by respective forwarding devices. SDN provides an easy and efficient management solutions for software-programmed consolidated middlebox in virtual machines. Additionally, SDN with centralized controller faces complications like scalability, network bottle neck, and single point failure. In this study, a stateful inspection firewall acts as a middlebox in distributed SDN-controlled network. The controller is programmed with a failure detection and recovery mechanism to provide reliability and redundancy and enhance the overall performance of the network. The objective of stateful firewall on SDN architecture is to secure the network by monitoring the current connections and maintain its state information until the connection is active. In this paper, the performance of firewall-enabled SDN with centralized and distributed controllers are measured, compared, and analyzed. The experiments are done using POX controller, and the results are verified by Mininet network emulation tool. The results show that the stateful firewall-enabled SDN with distributed controller network improves the security, reliability, availability, and overall performance of the network. In the proposed SDN, average network throughput is improved by 43%, average network delay is reduced by 4%, average channel utilization is increased by 40%, average network overhead is reduced by 26%, and average network response time is reduced by 23%. KEYWORDSdistributed controller, middlebox, OpenFlow, SDN, software-defined network, stateful firewall | INTRODUCTIONSoftware-defined network (SDN) is a promising network model that is utilized to build an adaptable and less expensive alternative for an existing network. SDN decouples the control plane and data plane from the forwarding device. The decoupled control planes from all the forwarding devices are centralized by the SDN controller. A single centralized controller network in SDN has issues like network bottle neck, which cause a single point network failure, less reliability, and scalability. Network bottle neck problem occurs in single centralized SDN controller when there is a rapid increase of ingress traffic. To solve the above-mentioned issue, distributed controllers are configured to handle ingress and egress

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%.