Papers
Topics
Authors
Recent
Search
2000 character limit reached

NetTiSA: Extended IP Flow with Time-series Features for Universal Bandwidth-constrained High-speed Network Traffic Classification

Published 9 Oct 2023 in cs.NI and cs.LG | (2310.05530v1)

Abstract: Network traffic monitoring based on IP Flows is a standard monitoring approach that can be deployed to various network infrastructures, even the large IPS-based networks connecting millions of people. Since flow records traditionally contain only limited information (addresses, transport ports, and amount of exchanged data), they are also commonly extended for additional features that enable network traffic analysis with high accuracy. Nevertheless, the flow extensions are often too large or hard to compute, which limits their deployment only to smaller-sized networks. This paper proposes a novel extended IP flow called NetTiSA (Network Time Series Analysed), which is based on the analysis of the time series of packet sizes. By thoroughly testing 25 different network classification tasks, we show the broad applicability and high usability of NetTiSA, which often outperforms the best-performing related works. For practical deployment, we also consider the sizes of flows extended for NetTiSA and evaluate the performance impacts of its computation in the flow exporter. The novel feature set proved universal and deployable to high-speed ISP networks with 100\,Gbps lines; thus, it enables accurate and widespread network security protection.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (38)
  1. doi:10.17487/RFC8446. URL https://www.rfc-editor.org/info/rfc8446
  2. doi:10.17487/RFC8484. URL https://www.rfc-editor.org/info/rfc8484
  3. doi:10.1145/3143361.3143399. URL https://doi.org/10.1145/3143361.3143399
  4. doi:10.17487/RFC7011.
  5. doi:10.17487/RFC3954. URL https://doi.org/10.17487/RFC3954
  6. doi:10.1109/COMST.2014.2321898.
  7. doi:10.1109/SURV.2010.032210.00054.
  8. doi:10.1109/ACCESS.2023.3275744.
  9. doi:10.1109/TIFS.2022.3183390.
  10. doi:10.1109/DASC-PICom-CBDCom-CyberSciTech52372.2021.00024.
  11. doi:10.1016/j.comnet.2022.109467.
  12. doi:10.23919/CNSM52442.2021.9615561.
  13. doi:10.1007/978-3-031-22295-5_8.
  14. arXiv:2307.13434.
  15. doi:10.5281/zenodo.8301043. URL https://doi.org/10.5281/zenodo.8301043
  16. doi:10.17487/RFC7858. URL https://www.rfc-editor.org/info/rfc7858
  17. doi:10.1016/j.jnca.2021.102985.
  18. doi:10.1145/3407023.3409192. URL https://doi.org/10.1145/3407023.3409192
  19. doi:10.1109/DASC-PICom-CBDCom-CyberSciTech49142.2020.00026.
  20. doi:10.1145/3133956.3134074. URL https://doi.org/10.1145/3133956.3134074
  21. doi:10.1145/3426020.3426093. URL https://doi.org/10.1145/3426020.3426093
  22. doi:10.4304/jcp.9.5.1234-1240.
  23. doi:10.1109/JIOT.2022.3228816.
  24. doi:https://doi.org/10.1016/j.cose.2014.05.011.
  25. doi:10.1007/978-3-319-99073-6_17.
  26. doi:10.5281/zenodo.4275775.
  27. doi:10.1109/CCWC51732.2021.9375998.
  28. doi:10.5281/zenodo.7189293.
  29. doi:https://doi.org/10.1016/j.dib.2022.108310.
  30. doi:10.1016/j.future.2019.05.041.
  31. doi:10.1016/j.future.2020.02.017.
  32. doi:10.5281/zenodo.4743746.
  33. doi:10.21227/mbc1-1h68.
  34. doi:10.5220/0006105602530262.
  35. arXiv:2205.05628, doi:10.48550/arXiv.2205.05628.
  36. doi:10.1109/SPW.2019.00019.
  37. L. Foundation, Data plane development kit (DPDK) (2015). URL http://www.dpdk.org
  38. doi:10.1109/ACCESS.2022.3165809.
Citations (4)

Summary

No one has generated a summary of this paper yet.

Paper to Video (Beta)

No one has generated a video about this paper yet.

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.