Assessment of Conflict Flows in Software-Defined Networks using a Novel Nature-Inspired Optimization-Tuned Kernelized SVM
Keywords:
Conflict Flow, Security, Software-Defined Network (SDN), Tree-Seed Optimization-Tuned Kernelized Support Vector Machine (TSO-KSVM)Abstract
The centralizing management and flexibly customizing network resources, Software-Defined Networks (SDN) completely transform network administration. As networks become more intricate, the likelihood of conflicts arising data flows increases, potentially leading to a decline in overall performance and the emergence of security vulnerabilities. This paper presents a tree-seed optimization-tuned kernelized support vector machine (TSO-KSVM) for the assessment of conflict flows in SDN environments. Initially, we gather data samples of SDN in conflict flows to analyze the performance of the proposed method. Applying the min-max scaling method to preprocess the raw data samples and linear discriminant analysis (LDA) is carried out to reduce the dimension. In the proposed framework, TSO is applied to enhance the assessment in the KSVM model. The proposed method is implemented in the Python tool. The proposed method's performance is analyzed in terms of various metrics compared with other methods. From the experimented results, we conclude that the proposed method attains the greatest accuracy rate of other methods in assessing conflict flows in SDN networks.
Downloads
References
. LUDWIG–MAXIMILIANS–UNIVERSIT, A. M. Experimental Examination of Distributed Conflicts in Software Defined Networks.
. Kafetzis, D., Vassilaras, S., Vardoulias, G., &Koutsopoulos, I. (2022). Software-defined networking meets software-defined radio in mobile ad hoc networks: state of the art and future directions. IEEE Access, 10, 9989-10014.
. Guidara, A., Pomares Hernandez, S. E., Rodriguez Henriquez, L. M. X., HadjKacem, H., &HadjKacem, A. (2020). Towards causal consistent updates in software-defined networks. Applied Sciences, 10(6), 2081.
. Khanmirza, H. (2022). WildMinnie: compression of software-defined networking (SDN) rules with wildcard patterns. PeerJ Computer Science, 8, e809.
. Häckel, T., Meyer, P., Korf, F., & Schmidt, T. C. (2022). Secure time-sensitive software-defined networking in vehicles. IEEE Transactions on Vehicular Technology, 72(1), 35-51.
. Tan, E., Chong, Y., & Anbar, M. F. (2022). Flow management mechanism in software-defined network. Comput. Mater. Cont, 1(70), 1437-1459.
. Ujcich, B. E., Jero, S., Skowyra, R., Gomez, S. R., Bates, A., Sanders, W. H., &Okhravi, H. (2020, January). Automated discovery of cross-plane event-based vulnerabilities in software-defined networking. In Network and Distributed System Security Symposium.
. Farooq, M. S., Riaz, S., &Alvi, A. (2023). Security and Privacy Issues in Software-Defined Networking (SDN): A Systematic Literature Review. Electronics, 12(14), 3077.
. Pang, Z., Huang, X., Li, Z., Zhang, S., Xu, Y., Wan, H., & Zhao, X. (2020). Flow scheduling for conflict-free network updates in time-sensitive software-defined networks. IEEE Transactions on Industrial Informatics, 17(3), 1668-1678.
. Tran, C. N., &Danciu, V. (2020). A general approach to conflict detection in software-defined networks. SN Computer Science, 1, 1-14.
. Khairi, M. H. H. (2021). Flow Conflict Eliminations through Machine Learning for Software Defined Network (Doctoral dissertation, Ph. D. dissertation, UniversitiTeknologi Malaysia).
. ZHANG, L., LIN, H., HUAN, W., & BI, W. (2022). Software defined network flow rule conflict detection system based on OpenFlow. Journal of Computer Applications, 42(2), 528.
. Asif, A. B., Imran, M., Shah, N., Afzal, M., &Khurshid, H. (2021). ROCA: Auto‐resolving overlapping and conflicts in Access Control List policies for Software Defined Networking. International Journal of Communication Systems, 34(9), e4815.
. Tran, C. N. (2022). Conflict detection in software-defined networks (Doctoral dissertation, lmu).
. Danciu, V., & Tran, C. N. (2020). Side-effects causing hidden conflicts in software-defined networks. SN Computer Science, 1(5), 278.
. Tang, L., Fu, Y., Zeng, Y., Li, Z., & Li, S. (2021). Flow entry conflict detection and resolution scheme for software-defined networking. The International Journal of Electrical Engineering & Education, 0020720921998237.
. Lee, S., Woo, S., Kim, J., Yegneswaran, V., Porras, P., & Shin, S. (2020, July). AudiSDN: Automated detection of network policy inconsistencies in software-defined networks. In IEEE INFOCOM 2020-IEEE Conference on Computer Communications (pp. 1788-1797). IEEE.
. Liu, Q., Cheng, L., Alves, R., Ozcelebi, T., Kuipers, F., Xu, G., ...& Chen, S. (2021). Cluster-based flow control in hybrid software-defined wireless sensor networks. Computer Networks, 187, 107788.
. Khairi, M. H., Abdalla, B. M. A., Hassan, M. K., Ariffin, S. H., &Hamdan, M. (2024). Utilizing Extremely Fast Decision Tree (EFDT) Algorithm to Categorize Conflict Flow on a Software-Defined Network (SDN) Controller. Engineering, Technology & Applied Science Research, 14(2), 13261-13265.
. Latah, M., &Toker, L. (2020). An efficient flow-based multi-level hybrid intrusion detection system for software-defined networks. CCF Transactions on Networking, 3(3-4), 261-271.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
