Abstract
Denial of service (DoS) attacks in Software-Defined Network (SDN) environments are increasing despite the capabilities and benefits of SDN. Software-based traffic analysis, centralized control and automatic information forwarding offered by SDN, makes it easier to detect and react effectively to DoS attacks; however, the security of the SDN itself has not yet been resolved, and there are a number of potential vulnerabilities not only of the DoS type, on the SDN platforms. In this document, we review some applications and defense mechanisms to mitigate these types of attacks in an SDN network environment. This work could help us to understand the advantages of SDNs compared to current network architectures, without leaving aside the security issue that will continue to be maintained over the years.
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References
Hong, K., Kim, Y., Choi, H., Park, J.: SDN-assisted slow HTTP DDoS attack defense method. IEEE Commun. Lett. 22(4), 688–691 (2018)
Alharbi, T., Portmann, M., Pakzad, F.: The (in)security of topology discovery in software defined networks. In: Proceedings of the Conference on Local Computer Networks (LCN), vol. 2629, pp. 502–505, Oct 2015
Bjorn, M.: Software Defined Networks (SDN) and its relevance in the DC, pp. 143 (2013)
Yan, Q., Yu, F.R., Gong, Q., Li, J.: Software-defined networking (SDN) and distributed denial of service (DDOS) attacks in cloud computing environments: a survey, some research issues, and challenges. IEEE Commun. Surv. Tutorials 18(1), 602–622 (2016)
Abdulqadder, I.H., Zou, D., Aziz, I.T., Yuan, B., Li, W.: SecSDN-cloud: defeating vulnerable attacks through secure software-defined networks. IEEE Access 6, 8292–8301 (2018)
Samson, A., Gopalan, N.P.: Software defined networking. In: Proceedings of the International Conference on Informatics and Analytics (ICIA 2016), pp. 16 (2016)
Aljuhani, A.: Virtualized network functions security attacks and vulnerabilities, pp. 1720 (2017)
Liu, Y., Lu, Y., Qiao, W., Chen, X.: A dynamic composition mechanism of security service chaining oriented to SDN/NFV-enabled networks. IEEE Access 6, 53918–53929 (2018)
Bellavista, P., Giannelli, C., Lagkas, T., Sarigiannidis, P.: Quality management of surveillance multimedia streams via federated SDN controllers in Fiwi-IoT integrated deployment environments. IEEE Access 6, 21324–21341 (2018)
Garcia, B.R.: OpenDaylight SDN controller platform A Degree Thesis Submitted to the Faculty of the Escola T’cnica d’ Enginyeria de Telecomunicacio de Barcelona Universitat Politsacnica de Catalunya by BERNAT RIBES GARCIA In partial fulfillment of the requirements for the, Oct 2015
Macias, J.: Evaluation of Service Denegation Attacks (DDos), Forms Of Protection in The Engineering Race in Computer Systems of The State University of The South of Manabid (2017)
Fawcett, L., Scott-Hayward, S., Broadbent, M., Wright, A., Race, N.: TENNISON: a distributed SDN framework for scalable network security. IEEE J. Sel. Areas Commun. 36(12), 2805–2818 (2018)
Paracuellos, J.: Proactive and reactive defense against DDoS attacks in a simulated environment of software-defined networks (2016)
Khondoker, A., Zaalouk, A., Marx, R., Bayarou, K.: Feature-based comparison and selection of Software Defined Networking (SDN) controllers. In: 2014 World Congress on Computer Applications and Information Systems (WCCAIS 2014), Jan 2014
Andr, D., Tutor, S.C., Carlos, J., Cebollada, G.: End work of grade Software Defined Networks (SDN): OpenFlow (2015)
Simpson, S., Shirazi, S.N., Marnerides, A., Jouet, S., Pezaros, D., Hutchison, D.: An inter-domain collaboration scheme to remedy DDoS attacks in computer networks. IEEE Trans. Netw. Serv. Manag. 15(3), 879–893 (2018)
Lawal, B.H., Nuray, A.T.: Real-time detection and mitigation of distributed denial of service (DDoS) attacks in software defined networking (SDN). In: 26th IEEE Signal Processing and Communication Application Conference (SIU 2018), pp. 14 (2018)
Sdn, S.N.: A Deep Learning Based DDoS Detection System, no. Dl, pp. 118
Hameed, S.: SDN based collaborative scheme for mitigation of DDoS attacks (2018)
Wang, A., Chen, S., Lakshman, T.V.: Scotch: elastically scaling up SDN control-plane using vSwitch based overlay, pp. 403–414 (2014)
Bhushan, K., Gupta, B.B.: ScienceDirect hypothesis test for low-rate DDoS attack detection in cloud computing environment. Procedia Comput. Sci. 132, 947–955 (2018)
Shafi, Q., Basit, A., Qaisar, S., Koay, A., Welch, I.: Fog-assisted SDN controlled framework for enduring anomaly detection in an IoT network. IEEE Access PP(c), 11 (2018)
Zhang, C., et al.: Towards SDN-based integrated architecture for mitigating IP spoofing attack. IEEE Access 6, 2764–2777 (2017)
Morillo Fueltala, D.G.: Implementation of a prototype of a software-defined network (SDN) using a software-based solution. In: XXV Days in Electrical and Electronic Ing, April 2016, pp. 356–365 (2014)
Boron, A., Project, O.: OpenDaylight Documentation Documentation (2016)
Guede, N.L.: OmniController. Coordinated Infrastructure SDN and OpenFlow (2015)
Xu, T., Gao, D., Dong, P., Zhang, H., Foh, C.H., Chao, H.C.: Defending against new-flow attack in SDN-based internet of things. IEEE Access 5, 3431–3443 (2017)
Aljuhani, A., Alharbi, T.: Virtualized network functions security attacks and vulnerabilities. In: 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC 2017), pp. 14 (2017)
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Dominguez-Limaico, M., Maya-Olalla, E., Bosmediano-Cardenas, C., Escobar-Teran, C., Chafla-Altamirano, J.F., Bedón-Chamorro, A. (2020). Machine Learning in an SDN Network Environment for DoS Attacks. In: Basantes-Andrade, A., Naranjo-Toro, M., Zambrano Vizuete, M., Botto-Tobar, M. (eds) Technology, Sustainability and Educational Innovation (TSIE). TSIE 2019. Advances in Intelligent Systems and Computing, vol 1110. Springer, Cham. https://doi.org/10.1007/978-3-030-37221-7_20
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