An adaptive detection and prevention architecture for unsafe traffic in SDN enabled mobile networks

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

3 Citations (Scopus)

Abstract

The forthcoming 5G cloud networks will utilize software defined networking (SDN) and network functions virtualization (NFV) to provide new services. However, applying these technologies introduce new threats to network. To detect the security attacks and malicious traffic both on end user and cloudified mobile network, we apply centralized monitoring and combine dynamicity and programmability of SDN, traffic filtering capabilities of IDS and clustering mechanisms for load balancing. We discuss and demonstrate an adaptive detection and prevention architecture for SDN enabled mobile networks.

Original languageEnglish
Title of host publicationProceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management
PublisherIEEE
Pages883-884
Number of pages2
ISBN (Electronic)9783901882890
DOIs
Publication statusPublished - 20 Jul 2017
MoE publication typeA4 Article in a conference publication
EventIFIP/IEEE International Symposium on Integrated Network and Service Management - Lisbon, Portugal
Duration: 8 May 201712 May 2017
Conference number: 15

Conference

ConferenceIFIP/IEEE International Symposium on Integrated Network and Service Management
Abbreviated titleIM
CountryPortugal
CityLisbon
Period08/05/201712/05/2017

Keywords

  • Anomaly Detection
  • Cloud
  • Controller
  • Detection as a Service
  • IDS
  • SDN
  • Security

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  • Cite this

    Monshizadeh, M., Khatri, V., & Kantola, R. (2017). An adaptive detection and prevention architecture for unsafe traffic in SDN enabled mobile networks. In Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management (pp. 883-884). [7987395] IEEE. https://doi.org/10.23919/INM.2017.7987395