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  • Open Access

    ARTICLE

    ProbD: Faulty Path Detection Based on Probability in Software-Defined Networking

    Jiangyuan Yao1, Jiawen Wang1, Shuhua Weng1, Minrui Wang1, Deshun Li1,*, Yahui Li2, Xingcan Cao3

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1783-1796, 2023, DOI:10.32604/iasc.2023.034265

    Abstract With the increasing number of switches in Software-Defined Networking (SDN), there are more and more faults rising in the data plane. However, due to the existence of link redundancy and multi-path forwarding mechanisms, these problems cannot be detected in time. The current faulty path detection mechanisms have problems such as the large scale of detection and low efficiency, which is difficult to meet the requirements of efficient faulty path detection in large-scale SDN. Concerning this issue, we propose an efficient network path fault testing model ProbD based on probability detection. This model achieves a high… More >

  • Open Access

    ARTICLE

    Adaptive Partial Task Offloading and Virtual Resource Placement in SDN/NFV-Based Network Softwarization

    Prohim Tam1, Sa Math1, Seokhoon Kim1,2,*

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 2141-2154, 2023, DOI:10.32604/csse.2023.030984

    Abstract Edge intelligence brings the deployment of applied deep learning (DL) models in edge computing systems to alleviate the core backbone network congestions. The setup of programmable software-defined networking (SDN) control and elastic virtual computing resources within network functions virtualization (NFV) are cooperative for enhancing the applicability of intelligent edge softwarization. To offer advancement for multi-dimensional model task offloading in edge networks with SDN/NFV-based control softwarization, this study proposes a DL mechanism to recommend the optimal edge node selection with primary features of congestion windows, link delays, and allocatable bandwidth capacities. Adaptive partial task offloading policy… More >

  • Open Access

    ARTICLE

    DoS Attack Detection Based on Deep Factorization Machine in SDN

    Jing Wang1, Xiangyu Lei1, Qisheng Jiang1, Osama Alfarraj2, Amr Tolba2, Gwang-jun Kim3,*

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1727-1742, 2023, DOI:10.32604/csse.2023.030183

    Abstract Software-Defined Network (SDN) decouples the control plane of network devices from the data plane. While alleviating the problems presented in traditional network architectures, it also brings potential security risks, particularly network Denial-of-Service (DoS) attacks. While many research efforts have been devoted to identifying new features for DoS attack detection, detection methods are less accurate in detecting DoS attacks against client hosts due to the high stealth of such attacks. To solve this problem, a new method of DoS attack detection based on Deep Factorization Machine (DeepFM) is proposed in SDN. Firstly, we select the Growth… More >

  • Open Access

    ARTICLE

    Detection Collision Flows in SDN Based 5G Using Machine Learning Algorithms

    Aqsa Aqdus1, Rashid Amin1,*, Sadia Ramzan1, Sultan S. Alshamrani2, Abdullah Alshehri3, El-Sayed M. El-kenawy4

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1413-1435, 2023, DOI:10.32604/cmc.2023.031719

    Abstract The rapid advancement of wireless communication is forming a hyper-connected 5G network in which billions of linked devices generate massive amounts of data. The traffic control and data forwarding functions are decoupled in software-defined networking (SDN) and allow the network to be programmable. Each switch in SDN keeps track of forwarding information in a flow table. The SDN switches must search the flow table for the flow rules that match the packets to handle the incoming packets. Due to the obvious vast quantity of data in data centres, the capacity of the flow table restricts… More >

  • Open Access

    ARTICLE

    A Novel Method for Routing Optimization in Software-Defined Networks

    Salem Alkhalaf*, Fahad Alturise

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6393-6405, 2022, DOI:10.32604/cmc.2022.031698

    Abstract Software-defined network (SDN) is a new form of network architecture that has programmability, ease of use, centralized control, and protocol independence. It has received high attention since its birth. With SDN network architecture, network management becomes more efficient, and programmable interfaces make network operations more flexible and can meet the different needs of various users. The mainstream communication protocol of SDN is OpenFlow, which contains a Match Field in the flow table structure of the protocol, which matches the content of the packet header of the data received by the switch, and completes the corresponding… More >

  • Open Access

    ARTICLE

    Dynamic Threshold-Based Approach to Detect Low-Rate DDoS Attacks on Software-Defined Networking Controller

    Mohammad Adnan Aladaileh, Mohammed Anbar*, Iznan H. Hasbullah, Abdullah Ahmed Bahashwan, Shadi Al-Sarawn

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1403-1416, 2022, DOI:10.32604/cmc.2022.029369

    Abstract The emergence of a new network architecture, known as Software Defined Networking (SDN), in the last two decades has overcome some drawbacks of traditional networks in terms of performance, scalability, reliability, security, and network management. However, the SDN is vulnerable to security threats that target its controller, such as low-rate Distributed Denial of Service (DDoS) attacks, The low-rate DDoS attack is one of the most prevalent attacks that poses a severe threat to SDN network security because the controller is a vital architecture component. Therefore, there is an urgent need to propose a detection approach… More >

  • Open Access

    ARTICLE

    Comprehensive DDoS Attack Classification Using Machine Learning Algorithms

    Olga Ussatova1,2, Aidana Zhumabekova1,*, Yenlik Begimbayeva2,3, Eric T. Matson4, Nikita Ussatov5

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 577-594, 2022, DOI:10.32604/cmc.2022.026552

    Abstract The fast development of Internet technologies ignited the growth of techniques for information security that protect data, networks, systems, and applications from various threats. There are many types of threats. The dedicated denial of service attack (DDoS) is one of the most serious and widespread attacks on Internet resources. This attack is intended to paralyze the victim's system and cause the service to fail. This work is devoted to the classification of DDoS attacks in the special network environment called Software-Defined Networking (SDN) using machine learning algorithms. The analyzed dataset included instances of two classes:… More >

  • Open Access

    ARTICLE

    An Efficient Intrusion Detection Framework in Software-Defined Networking for Cybersecurity Applications

    Ghalib H. Alshammri1,2, Amani K. Samha3, Ezz El-Din Hemdan4, Mohammed Amoon1,4, Walid El-Shafai5,6,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3529-3548, 2022, DOI:10.32604/cmc.2022.025262

    Abstract Network management and multimedia data mining techniques have a great interest in analyzing and improving the network traffic process. In recent times, the most complex task in Software Defined Network (SDN) is security, which is based on a centralized, programmable controller. Therefore, monitoring network traffic is significant for identifying and revealing intrusion abnormalities in the SDN environment. Consequently, this paper provides an extensive analysis and investigation of the NSL-KDD dataset using five different clustering algorithms: K-means, Farthest First, Canopy, Density-based algorithm, and Exception-maximization (EM), using the Waikato Environment for Knowledge Analysis (WEKA) software to compare… More >

  • Open Access

    ARTICLE

    Optimized Load Balancing Technique for Software Defined Network

    Aashish Kumar1, Darpan Anand1, Sudan Jha2, Gyanendra Prasad Joshi3, Woong Cho4,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1409-1426, 2022, DOI:10.32604/cmc.2022.024970

    Abstract Software-defined networking is one of the progressive and prominent innovations in Information and Communications Technology. It mitigates the issues that our conventional network was experiencing. However, traffic data generated by various applications is increasing day by day. In addition, as an organization's digital transformation is accelerated, the amount of information to be processed inside the organization has increased explosively. It might be possible that a Software-Defined Network becomes a bottleneck and unavailable. Various models have been proposed in the literature to balance the load. However, most of the works consider only limited parameters and do More >

  • Open Access

    ARTICLE

    Ensemble Deep Learning Models for Mitigating DDoS Attack in Software-Defined Network

    Fatmah Alanazi*, Kamal Jambi, Fathy Eassa, Maher Khemakhem, Abdullah Basuhail, Khalid Alsubhi

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 923-938, 2022, DOI:10.32604/iasc.2022.024668

    Abstract Software-defined network (SDN) is an enabling technology that meets the demand of dynamic, adaptable, and manageable networking architecture for the future. In contrast to the traditional networks that are based on a distributed control plane, the control plane of SDN is based on a centralized architecture. As a result, SDNs are susceptible to critical cyber attacks that exploit the single point of failure. A distributed denial of service (DDoS) attack is one of the most crucial and risky attacks, targeting the SDN controller and disrupting its services. Several researchers have proposed signature-based DDoS mitigation and… More >

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