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

Mehrnoosh Monshizadeh, Vikramajeet Khatri, Raimo Kantola

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

    10 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 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
    Country/TerritoryPortugal
    CityLisbon
    Period08/05/201712/05/2017

    Keywords

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

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