Hira Akhtar Butt¹, Khoula Said Al Harthy², Mumtaz Ali Shah³, Mudassar Hussain^2,*, Rashid Amin^4,*, Mujeeb Ur Rehman¹

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3003-3031, 2024, DOI:10.32604/cmc.2024.057185 - 18 November 2024

Abstract Detecting sophisticated cyberattacks, mainly Distributed Denial of Service (DDoS) attacks, with unexpected patterns remains challenging in modern networks. Traditional detection systems often struggle to mitigate such attacks in conventional and software-defined networking (SDN) environments. While Machine Learning (ML) models can distinguish between benign and malicious traffic, their limited feature scope hinders the detection of new zero-day or low-rate DDoS attacks requiring frequent retraining. In this paper, we propose a novel DDoS detection framework that combines Machine Learning (ML) and Ensemble Learning (EL) techniques to improve DDoS attack detection and mitigation in SDN environments. Our model… More >

Jinlin Xu^1,2, Wansu Pan^1,*, Haibo Tan^1,2, Longle Cheng¹, Xiaofeng Li^1,2

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2709-2726, 2024, DOI:10.32604/cmc.2024.056925 - 18 November 2024

Abstract The traffic within data centers exhibits bursts and unpredictable patterns. This rapid growth in network traffic has two consequences: it surpasses the inherent capacity of the network’s link bandwidth and creates an imbalanced network load. Consequently, persistent overload situations eventually result in network congestion. The Software Defined Network (SDN) technology is employed in data centers as a network architecture to enhance performance. This paper introduces an adaptive congestion control strategy, named DA-DCTCP, for SDN-based Data Centers. It incorporates Explicit Congestion Notification (ECN) and Round-Trip Time (RTT) to establish congestion awareness and an ECN marking model.… More >

Ahmad Rahdari^1,6, Ahmad Jalili², Mehdi Esnaashari³, Mehdi Gheisari^1,4,7,8,*, Alisa A. Vorobeva⁵, Zhaoxi Fang¹, Panjun Sun^1,*, Viktoriia M. Korzhuk⁵, Ilya Popov⁵, Zongda Wu¹, Hamid Tahaei¹

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2511-2533, 2024, DOI:10.32604/cmc.2024.052994 - 15 August 2024

Abstract Software-Defined Networking (SDN) represents a significant paradigm shift in network architecture, separating network logic from the underlying forwarding devices to enhance flexibility and centralize deployment. Concurrently, the Internet of Things (IoT) connects numerous devices to the Internet, enabling autonomous interactions with minimal human intervention. However, implementing and managing an SDN-IoT system is inherently complex, particularly for those with limited resources, as the dynamic and distributed nature of IoT infrastructures creates security and privacy challenges during SDN integration. The findings of this study underscore the primary security and privacy challenges across application, control, and data planes.… More >

Johari Abdul Rahim¹, Rosdiadee Nordin^2,*, Oluwatosin Ahmed Amodu^3,4

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 747-800, 2024, DOI:10.32604/cmc.2024.047009 - 18 July 2024

Abstract Software Defined Networking (SDN) is programmable by separation of forwarding control through the centralization of the controller. The controller plays the role of the ‘brain’ that dictates the intelligent part of SDN technology. Various versions of SDN controllers exist as a response to the diverse demands and functions expected of them. There are several SDN controllers available in the open market besides a large number of commercial controllers; some are developed to meet carrier-grade service levels and one of the recent trends in open-source SDN controllers is the Open Network Operating System (ONOS). This paper… More >

Meignanamoorthi Dhandapani^*, V. Vetriselvi, R. Aishwarya

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2449-2486, 2024, DOI:10.32604/cmes.2024.050986 - 08 July 2024

Abstract The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global scale. Network slicing is crucial in delivering services for different, demanding vertical applications in this context. Next-generation applications have time-sensitive requirements and depend on the most efficient routing path to ensure packets reach their intended destinations. However, the existing IP (Internet Protocol) over a multi-domain network faces challenges in enforcing network slicing due to minimal collaboration and information sharing among network operators. Conventional inter-domain routing methods, like Border Gateway Protocol (BGP), cannot make routing decisions based on performance,… More >

Yu Song¹, Xusheng Qian², Nan Zhang³, Wei Wang², Ao Xiong^1,*

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3007-3021, 2024, DOI:10.32604/cmc.2024.051217 - 15 May 2024

Abstract To enhance the efficiency and expediency of issuing e-licenses within the power sector, we must confront the challenge of managing the surging demand for data traffic. Within this realm, the network imposes stringent Quality of Service (QoS) requirements, revealing the inadequacies of traditional routing allocation mechanisms in accommodating such extensive data flows. In response to the imperative of handling a substantial influx of data requests promptly and alleviating the constraints of existing technologies and network congestion, we present an architecture for QoS routing optimization with in Software Defined Network (SDN), leveraging deep reinforcement learning. This… More >

Jinlin Xu^1,2, Wansu Pan^1,*, Longle Cheng^1,2, Haibo Tan^1,2, Munan Yuan^1,*, Xiaofeng Li^1,2

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1399-1418, 2024, DOI:10.32604/cmc.2024.049622 - 25 April 2024

Abstract The existing multipath routing in Software Defined Network (SDN) is relatively blind and inefficient, and there is a lack of cooperation between the terminal and network sides, making it difficult to achieve dynamic adaptation of service requirements and network resources. To address these issues, we propose a multi-constraint path optimization scheme based on information fusion in SDN. The proposed scheme collects network topology and network state information on the network side and computes disjoint paths between end hosts. It uses the Fuzzy Analytic Hierarchy Process (FAHP) to calculate the weight coefficients of multiple constrained parameters… More >

Nasser Alshammari¹, Shumaila Shahzadi², Saad Awadh Alanazi^1,*, Shahid Naseem³, Muhammad Anwar³, Madallah Alruwaili⁴, Muhammad Rizwan Abid⁵, Omar Alruwaili⁴, Ahmed Alsayat¹, Fahad Ahmad^6,7

Computer Systems Science and Engineering, Vol.48, No.2, pp. 363-394, 2024, DOI:10.32604/csse.2023.040721 - 19 March 2024

Abstract Software Defined Network (SDN) and Network Function Virtualization (NFV) technology promote several benefits to network operators, including reduced maintenance costs, increased network operational performance, simplified network lifecycle, and policies management. Network vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration (NFV MANO), and malicious attacks in different scenarios disrupt the NFV Orchestrator (NFVO) and Virtualized Infrastructure Manager (VIM) lifecycle management related to network services or individual Virtualized Network Function (VNF). This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and… More >

Laila M. Halman, Mohammed J. F. Alenazi^*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1469-1483, 2024, DOI:10.32604/cmes.2023.028077 - 17 November 2023

Abstract The healthcare sector holds valuable and sensitive data. The amount of this data and the need to handle, exchange, and protect it, has been increasing at a fast pace. Due to their nature, software-defined networks (SDNs) are widely used in healthcare systems, as they ensure effective resource utilization, safety, great network management, and monitoring. In this sector, due to the value of the data, SDNs face a major challenge posed by a wide range of attacks, such as distributed denial of service (DDoS) and probe attacks. These attacks reduce network performance, causing the degradation of… More > Graphic Abstract

Gul Nawaz¹, Muhammad Junaid¹, Adnan Akhunzada², Abdullah Gani^2,*, Shamyla Nawazish³, Asim Yaqub³, Adeel Ahmed¹, Huma Ajab⁴

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2157-2178, 2023, DOI:10.32604/cmc.2023.026952 - 29 November 2023

Abstract Distributed denial of service (DDoS) attack is the most common attack that obstructs a network and makes it unavailable for a legitimate user. We proposed a deep neural network (DNN) model for the detection of DDoS attacks in the Software-Defined Networking (SDN) paradigm. SDN centralizes the control plane and separates it from the data plane. It simplifies a network and eliminates vendor specification of a device. Because of this open nature and centralized control, SDN can easily become a victim of DDoS attacks. We proposed a supervised Developed Deep Neural Network (DDNN) model that can… More >