software defined networking
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Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 431
Author(s):  
Martina Troscia ◽  
Andrea Sgambelluri ◽  
Francesco Paolucci ◽  
Piero Castoldi ◽  
Paolo Pagano ◽  
...  

Software Defined Networking represents a mature technology for the control of optical networks, though all open controller implementations present in the literature still lack the adequate level of maturity and completeness to be considered for (pre)-production network deployments. This work aims at experimenting on, assessing and discussing the use of the OneM2M open-source platform in the context of optical networks. Network elements and devices are implemented as IoT devices, and the control application is built on top of an OneM2M-compliant server. The work concretely addresses the scalability and flexibility performances of the proposed solution, accounting for the expected growth of optical networks. The two experiment scenarios show promising results and confirm that the OneM2M platform can be adopted in such a context, paving the way to other researches and studies.


2022 ◽  
pp. 19-38
Author(s):  
Muhammad Junaid Nazar ◽  
Saleem Iqbal ◽  
Saud Altaf ◽  
Kashif Naseer Qureshi ◽  
Khalid Hussain Usmani ◽  
...  

2022 ◽  
Vol 70 (1) ◽  
pp. 1349-1362
Author(s):  
Nancy Abbas El-Hefnawy ◽  
Osama Abdel Raouf ◽  
Heba Askr

2022 ◽  
Vol 70 (1) ◽  
pp. 1363-1379
Author(s):  
Shabir Ahmad ◽  
Faisal Jamil ◽  
Abid Ali ◽  
Ehtisham Khan ◽  
Muhammad Ibrahim ◽  
...  

2021 ◽  
Vol 12 (1) ◽  
pp. 370
Author(s):  
Cong Fan ◽  
Nitheesh Murugan Kaliyamurthy ◽  
Shi Chen ◽  
He Jiang ◽  
Yiwen Zhou ◽  
...  

Software Defined Networking (SDN) is one of the most commonly used network architectures in recent years. With the substantial increase in the number of Internet users, network security threats appear more frequently, which brings more concerns to SDN. Distributed denial of Service (DDoS) attacks are one of the most dangerous and frequent attacks in software defined networks. The traditional attack detection method using entropy has some defects such as slow attack detection and poor detection effect. In order to solve this problem, this paper proposed a method of fusion entropy, which detects attacks by measuring the randomness of network events. This method has the advantages of fast attack detection speed and obvious decrease in entropy value. The complementarity of information entropy and log energy entropy is effectively utilized. The experimental results show that the entropy value of the attack scenarios 91.25% lower than normal scenarios, which has greater advantages and significance compared with other attack detection methods.


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