Security and Performance Modeling and Optimization for Software Defined Networking

Taehoon Eom, Jin Hong, Seongmo An, Jong Sou Park, Dong Seong Kim

Research output: Chapter in Book/Conference paperConference paper

Abstract

Software Defined Networking (SDN) provides new functionalities to efficiently manage the network traffic, which can be used to enhance the networking capabilities to support the growing communication demands today. But at the same time, it introduces new attack vectors that can be exploited by attackers. Hence, evaluating and selecting countermeasures to optimize the security of the SDN is of paramount importance. However, one should also take into account the trade-off between security and performance of the SDN. In this paper, we present a security optimization approach for the SDN taking into account the trade-off between security and performance. We evaluate the security of the SDN using graphical security models and metrics, and use queuing models to measure the performance of the SDN. Further, we use Genetic Algorithms, namely NSGA-II, to optimally select the countermeasure with performance and security constraints. Our experimental analysis results show that the proposed approach can efficiently compute the countermeasures that will optimize the security of the SDN while satisfying the performance constraints.
Original languageEnglish
Title of host publicationProceedings 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages610-617
Number of pages8
ISBN (Electronic)978-1-7281-2777-4
ISBN (Print)978-1-7281-2778-1
DOIs
Publication statusPublished - 2019
Event18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE 2019) - Rotorua, New Zealand
Duration: 5 Aug 20198 Aug 2019

Conference

Conference18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE 2019)
Abbreviated titleTrustCom/BigDataSE 2019
CountryNew Zealand
CityRotorua
Period5/08/198/08/19

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Computer simulation
Software defined networking
Genetic algorithms
Communication

Cite this

Eom, T., Hong, J., An, S., Park, J. S., & Kim, D. S. (2019). Security and Performance Modeling and Optimization for Software Defined Networking. In Proceedings 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE) (pp. 610-617). United States: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/TrustCom/BigDataSE.2019.00087
Eom, Taehoon ; Hong, Jin ; An, Seongmo ; Park, Jong Sou ; Kim, Dong Seong. / Security and Performance Modeling and Optimization for Software Defined Networking. Proceedings 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). United States : IEEE, Institute of Electrical and Electronics Engineers, 2019. pp. 610-617
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title = "Security and Performance Modeling and Optimization for Software Defined Networking",
abstract = "Software Defined Networking (SDN) provides new functionalities to efficiently manage the network traffic, which can be used to enhance the networking capabilities to support the growing communication demands today. But at the same time, it introduces new attack vectors that can be exploited by attackers. Hence, evaluating and selecting countermeasures to optimize the security of the SDN is of paramount importance. However, one should also take into account the trade-off between security and performance of the SDN. In this paper, we present a security optimization approach for the SDN taking into account the trade-off between security and performance. We evaluate the security of the SDN using graphical security models and metrics, and use queuing models to measure the performance of the SDN. Further, we use Genetic Algorithms, namely NSGA-II, to optimally select the countermeasure with performance and security constraints. Our experimental analysis results show that the proposed approach can efficiently compute the countermeasures that will optimize the security of the SDN while satisfying the performance constraints.",
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Eom, T, Hong, J, An, S, Park, JS & Kim, DS 2019, Security and Performance Modeling and Optimization for Software Defined Networking. in Proceedings 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). IEEE, Institute of Electrical and Electronics Engineers, United States, pp. 610-617, 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE 2019), Rotorua, New Zealand, 5/08/19. https://doi.org/10.1109/TrustCom/BigDataSE.2019.00087

Security and Performance Modeling and Optimization for Software Defined Networking. / Eom, Taehoon; Hong, Jin; An, Seongmo; Park, Jong Sou; Kim, Dong Seong.

Proceedings 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). United States : IEEE, Institute of Electrical and Electronics Engineers, 2019. p. 610-617.

Research output: Chapter in Book/Conference paperConference paper

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AU - Park, Jong Sou

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PY - 2019

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N2 - Software Defined Networking (SDN) provides new functionalities to efficiently manage the network traffic, which can be used to enhance the networking capabilities to support the growing communication demands today. But at the same time, it introduces new attack vectors that can be exploited by attackers. Hence, evaluating and selecting countermeasures to optimize the security of the SDN is of paramount importance. However, one should also take into account the trade-off between security and performance of the SDN. In this paper, we present a security optimization approach for the SDN taking into account the trade-off between security and performance. We evaluate the security of the SDN using graphical security models and metrics, and use queuing models to measure the performance of the SDN. Further, we use Genetic Algorithms, namely NSGA-II, to optimally select the countermeasure with performance and security constraints. Our experimental analysis results show that the proposed approach can efficiently compute the countermeasures that will optimize the security of the SDN while satisfying the performance constraints.

AB - Software Defined Networking (SDN) provides new functionalities to efficiently manage the network traffic, which can be used to enhance the networking capabilities to support the growing communication demands today. But at the same time, it introduces new attack vectors that can be exploited by attackers. Hence, evaluating and selecting countermeasures to optimize the security of the SDN is of paramount importance. However, one should also take into account the trade-off between security and performance of the SDN. In this paper, we present a security optimization approach for the SDN taking into account the trade-off between security and performance. We evaluate the security of the SDN using graphical security models and metrics, and use queuing models to measure the performance of the SDN. Further, we use Genetic Algorithms, namely NSGA-II, to optimally select the countermeasure with performance and security constraints. Our experimental analysis results show that the proposed approach can efficiently compute the countermeasures that will optimize the security of the SDN while satisfying the performance constraints.

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Eom T, Hong J, An S, Park JS, Kim DS. Security and Performance Modeling and Optimization for Software Defined Networking. In Proceedings 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). United States: IEEE, Institute of Electrical and Electronics Engineers. 2019. p. 610-617 https://doi.org/10.1109/TrustCom/BigDataSE.2019.00087