Software-Defined Networking (SDN): A Review

Waseem, Quadri; Din, Wan Isni Sofiah Wan; Aminuddin, Afrig; Mohammed, Muzammil H; Aziza, Rifda Faticha Alfa

doi:10.1109/icoiact55506.2022.9972067

Cited by 13 publications

(3 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…DDoS attacks exert specific impacts on SDN networks [5]. SDN networks might exhibit heightened vulnerability to attacks targeting the centralized controller that governs them.…”

Section: Issn: 2302-9285 mentioning

confidence: 99%

Detection and mitigation of DDoS attacks in SDN based intrusion detection system

Chouikik,

Ouaissa,

Ouaissa

et al. 2024

Bulletin EEI

View full text Add to dashboard Cite

Software defined networks (SDN) have completely revolutionized the management and operation of networks. This novel technology entails a distinctive approach to management. Amidst the advancements, a notable security concern arises in the form of distributed denial of service (DDoS) attacks. To counteract this attack, the deployment of intrusion detection systems (IDS) assumes paramount importance. IDS plays a critical role in monitoring network traffic, promptly detecting irregularities that may signify a potential denial of service (DoS) assault. This study delves into a comprehensive exploration of a DDoS attack on an SDN network using the OpenDaylight controller and the Mininet emulator. Furthermore, the assessment extends to evaluating the DDoS attack's repercussions and the effectiveness of IDS in mitigating such risks. Various performance metrics, including throughput according to delay time, are monitored to gauge network performance under duress. The difference in throughput curves when comparing scenarios with and without IDS highlights the significant impact of intrusion detection. When the IDS was absent, there was a noticeable increase in oscillations, indicating greater network susceptibility. On the other hand, the presence of an IDS created a more regulated environment, reducing variances and promoting a more stable network.

show abstract

“…DDoS attacks exert specific impacts on SDN networks [5]. SDN networks might exhibit heightened vulnerability to attacks targeting the centralized controller that governs them.…”

Section: Issn: 2302-9285 mentioning

confidence: 99%

Detection and mitigation of DDoS attacks in SDN based intrusion detection system

Chouikik,

Ouaissa,

Ouaissa

et al. 2024

Bulletin EEI

View full text Add to dashboard Cite

show abstract

“…Also, Garg et al utilized software‐defined networking (SDN) with the Internet of Things (IoT), and analyzed their behavior, topologies, security, and privacy 16 . Waseem et al 17 introduced a detailed review of SDN in the form of history, overview, architecture, benefits, services, trends, application, features, and challenges. Likewise, Sadkhan 18 defined the SDN, and described its contribution to network administration, as well as the security issues and challenges facing this technology.…”

Section: Related Workmentioning

confidence: 99%

SSHS: SDN seamless handover system among LAN access points

Abbas

Alenazi

2023

Concurrency and Computation

View full text Add to dashboard Cite

SummaryIn recent years, artificial intelligence techniques, such as software‐defined networks (SDNs), machine learning classification (ML classification), and mobility models (MMs), have become vital in developing networks. Furthermore, communication methodologies, such as handover, directly affect network performance. In this paper, we propose a new system named SSHS, SDN Seamless Handover System, that combines SDN with an ML classifier to administer the network connection of mobile nodes. Through the SSHS system, the SDN will centralize the control to enable comprehensive management over the network, coupled with a decision tree (DT) classifier in the RYU controller to bring intelligence to the SDN application by enabling data analysis and prediction among mobile nodes generated by the RSSGM model. We present the SSHS model's effectiveness in providing a seamless communication handover among multiple access points (APs). The results of this study revealed that the SSHS provided a seamless handover among APs by improving the throughput by 26%, and decreasing the delay of arriving packets by 73% to standard SDN handover system.

show abstract

“…According to previous research, the SIR model is used to predict and control a pandemic [2]- [9]. However, the pandemic SIR pandemic model has a problem because the transmission rate and recovery rate in the SIR model are constant [10]- [16]. Using these constants in predicting the number of infected and recovered is unsuitable for a condition that does not restrict population movement [17]- [22].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Transmission Rate and Recovery Rate of SIR Pandemic Model Using Kalman Filter

Putra¹,

Aminuddin²,

Purwanto³

et al. 2022

IJACSA

View full text Add to dashboard Cite

COVID-19 is a global pandemic that significantly impacts all aspects. The number of victims who died makes this disease so terrible. Various policies continue to be pursued to reduce the spread and impact of COVID-19. The spread of a disease can be modeled in differential equation modeling. This differential equation modeling is known as the SIR Model. A differential equation can be expressed in a state-space model. The state-space model is a model that is widely used to design a modern control system. This research carried out the transmission rate and recovery rate estimates in the SIR pandemic model. Estimation of the transmission rate and recovery rate in this study poses a challenge to the value of the number of people confirmed as infected. The experimental result shows that the transmission and recovery rates can be estimated using the data for the infected and recovered persons. Estimates of infected and recovered people were conducted using the Kalman Filter.

show abstract

Software-Defined Networking (SDN): A Review

Cited by 13 publications

References 35 publications

Detection and mitigation of DDoS attacks in SDN based intrusion detection system

Detection and mitigation of DDoS attacks in SDN based intrusion detection system

SSHS: SDN seamless handover system among LAN access points

Estimation of Transmission Rate and Recovery Rate of SIR Pandemic Model Using Kalman Filter

Contact Info

Product

Resources

About