A Security Assessment Mechanism for Software-Defined Networking-Based Mobile Networks
AbstractSoftware-Defined Networking-based Mobile Networks (SDN-MNs) are considered the future of 5G mobile network architecture. With the evolving cyber-attack threat, security assessments need to be performed in the network management. Due to the distinctive features of SDN-MNs, such as their dynamic nature and complexity, traditional network security assessment methodologies cannot be applied directly to SDN-MNs, and a novel security assessment methodology is needed. In this paper, an effective security assessment mechanism based on attack graphs and an Analytic Hierarchy Process (AHP) is proposed for SDN-MNs. Firstly, this paper discusses the security assessment problem of SDN-MNs and proposes a methodology using attack graphs and AHP. Secondly, to address the diversity and complexity of SDN-MNs, a novel attack graph definition and attack graph generation algorithm are proposed. In order to quantify security levels, the Node Minimal Effort (NME) is defined to quantify attack cost and derive system security levels based on NME. Thirdly, to calculate the NME of an attack graph that takes the dynamic factors of SDN-MN into consideration, we use AHP integrated with the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) as the methodology. Finally, we offer a case study to validate the proposed methodology. The case study and evaluation show the advantages of the proposed security assessment mechanism. View Full-Text
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Luo, S.; Dong, M.; Ota, K.; Wu, J.; Li, J. A Security Assessment Mechanism for Software-Defined Networking-Based Mobile Networks. Sensors 2015, 15, 31843-31858.
Luo S, Dong M, Ota K, Wu J, Li J. A Security Assessment Mechanism for Software-Defined Networking-Based Mobile Networks. Sensors. 2015; 15(12):31843-31858.Chicago/Turabian Style
Luo, Shibo; Dong, Mianxiong; Ota, Kaoru; Wu, Jun; Li, Jianhua. 2015. "A Security Assessment Mechanism for Software-Defined Networking-Based Mobile Networks." Sensors 15, no. 12: 31843-31858.