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Using of NLP Methods to Separate Traffic Packets of Different Protocols. / Rusinova, Zalina; Chernyshov, Yury.
Proceedings - 2023 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2023: book. Institute of Electrical and Electronics Engineers Inc., 2023. p. 344-347.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Harvard

Rusinova, Z & Chernyshov, Y 2023, Using of NLP Methods to Separate Traffic Packets of Different Protocols. in Proceedings - 2023 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2023: book. Institute of Electrical and Electronics Engineers Inc., pp. 344-347, 2023 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT), Екатеринбург, Russian Federation, 15/05/2023. https://doi.org/10.1109/USBEREIT58508.2023.10158858

APA

Rusinova, Z., & Chernyshov, Y. (2023). Using of NLP Methods to Separate Traffic Packets of Different Protocols. In Proceedings - 2023 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2023: book (pp. 344-347). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/USBEREIT58508.2023.10158858

Vancouver

Rusinova Z, Chernyshov Y. Using of NLP Methods to Separate Traffic Packets of Different Protocols. In Proceedings - 2023 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2023: book. Institute of Electrical and Electronics Engineers Inc. 2023. p. 344-347 doi: 10.1109/USBEREIT58508.2023.10158858

Author

Rusinova, Zalina ; Chernyshov, Yury. / Using of NLP Methods to Separate Traffic Packets of Different Protocols. Proceedings - 2023 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2023: book. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 344-347

BibTeX

@inproceedings{943bdebdd2b94cbab75d7bcf5264de7a,
title = "Using of NLP Methods to Separate Traffic Packets of Different Protocols",
abstract = "Trace analysis is a protocol reverse engineering technique that aims to determine the behavior of unknown network protocols by examining network messages. One of the possible steps in the trace analysis may be to divide the traffic dump into separate groups in accordance with the protocol stacks of the packets. In this article, we propose an unsupervised learning method in which we use NLP approaches to get package embeddings and then divide them into groups using clustering. This method can be applied to raw packet data and does not require any domain knowledge to extract the relevant features. The results show that the obtained embeddings successfully capture the semantic information underlying the protocols and allow us to divide the traffic dump into clusters containing packets with the same protocol stack. The developed method of grouping network packets makes it possible to increase the efficiency of the network packet analysis process by jointly analyzing packets belonging to the same unknown protocol.",
author = "Zalina Rusinova and Yury Chernyshov",
year = "2023",
month = may,
day = "15",
doi = "10.1109/USBEREIT58508.2023.10158858",
language = "English",
pages = "344--347",
booktitle = "Proceedings - 2023 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",
note = "2023 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT) ; Conference date: 15-05-2023 Through 17-05-2023",

}

RIS

TY - GEN

T1 - Using of NLP Methods to Separate Traffic Packets of Different Protocols

AU - Rusinova, Zalina

AU - Chernyshov, Yury

PY - 2023/5/15

Y1 - 2023/5/15

N2 - Trace analysis is a protocol reverse engineering technique that aims to determine the behavior of unknown network protocols by examining network messages. One of the possible steps in the trace analysis may be to divide the traffic dump into separate groups in accordance with the protocol stacks of the packets. In this article, we propose an unsupervised learning method in which we use NLP approaches to get package embeddings and then divide them into groups using clustering. This method can be applied to raw packet data and does not require any domain knowledge to extract the relevant features. The results show that the obtained embeddings successfully capture the semantic information underlying the protocols and allow us to divide the traffic dump into clusters containing packets with the same protocol stack. The developed method of grouping network packets makes it possible to increase the efficiency of the network packet analysis process by jointly analyzing packets belonging to the same unknown protocol.

AB - Trace analysis is a protocol reverse engineering technique that aims to determine the behavior of unknown network protocols by examining network messages. One of the possible steps in the trace analysis may be to divide the traffic dump into separate groups in accordance with the protocol stacks of the packets. In this article, we propose an unsupervised learning method in which we use NLP approaches to get package embeddings and then divide them into groups using clustering. This method can be applied to raw packet data and does not require any domain knowledge to extract the relevant features. The results show that the obtained embeddings successfully capture the semantic information underlying the protocols and allow us to divide the traffic dump into clusters containing packets with the same protocol stack. The developed method of grouping network packets makes it possible to increase the efficiency of the network packet analysis process by jointly analyzing packets belonging to the same unknown protocol.

UR - http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85164937218

U2 - 10.1109/USBEREIT58508.2023.10158858

DO - 10.1109/USBEREIT58508.2023.10158858

M3 - Conference contribution

SP - 344

EP - 347

BT - Proceedings - 2023 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT)

Y2 - 15 May 2023 through 17 May 2023

ER -

ID: 41986195