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Variable Length Field Detection Algorithm for Zero Knowledge Complex Network Traffic Analysis. / Sinadskiy, Alexey; Domukhovskii, Nikolai.
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. 324-327.

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

Harvard

Sinadskiy, A & Domukhovskii, N 2023, Variable Length Field Detection Algorithm for Zero Knowledge Complex Network Traffic Analysis. 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. 324-327, 2023 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT), 15/05/2023. https://doi.org/10.1109/USBEREIT58508.2023.10158856

APA

Sinadskiy, A., & Domukhovskii, N. (2023). Variable Length Field Detection Algorithm for Zero Knowledge Complex Network Traffic Analysis. In Proceedings - 2023 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2023: book (pp. 324-327). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/USBEREIT58508.2023.10158856

Vancouver

Sinadskiy A, Domukhovskii N. Variable Length Field Detection Algorithm for Zero Knowledge Complex Network Traffic Analysis. 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. 324-327 doi: 10.1109/USBEREIT58508.2023.10158856

Author

Sinadskiy, Alexey ; Domukhovskii, Nikolai. / Variable Length Field Detection Algorithm for Zero Knowledge Complex Network Traffic Analysis. 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. 324-327

BibTeX

@inproceedings{32b88df2e17d4c158ae9a0db1092e956,
title = "Variable Length Field Detection Algorithm for Zero Knowledge Complex Network Traffic Analysis",
abstract = "The article describes a method for restoring the structure of network traffic with zero prior knowledge. The importance of the problem being solved is explained (government authorities requirements and recent incidents in the field of information security). A brief description of the existing approaches is given. The general architecture of the proposed method based on the previous research of the authors is described [5]. Incoming packets are divided into groups according to the format of the transmitted data, for each group a prediction is made of the presence of a field boundary for each offset inside the packet. Groups of packets with a prediction confidence value less than the specified one are processed by a method working with variable-length fields using the ideas of genetic algorithms: mutations are selected iteratively for a set of proposed boundaries, a quality metric is calculated for each mutation, the best mutations are transferred to the next step.",
author = "Alexey Sinadskiy and Nikolai Domukhovskii",
year = "2023",
month = may,
day = "15",
doi = "10.1109/USBEREIT58508.2023.10158856",
language = "English",
pages = "324--327",
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 - Variable Length Field Detection Algorithm for Zero Knowledge Complex Network Traffic Analysis

AU - Sinadskiy, Alexey

AU - Domukhovskii, Nikolai

PY - 2023/5/15

Y1 - 2023/5/15

N2 - The article describes a method for restoring the structure of network traffic with zero prior knowledge. The importance of the problem being solved is explained (government authorities requirements and recent incidents in the field of information security). A brief description of the existing approaches is given. The general architecture of the proposed method based on the previous research of the authors is described [5]. Incoming packets are divided into groups according to the format of the transmitted data, for each group a prediction is made of the presence of a field boundary for each offset inside the packet. Groups of packets with a prediction confidence value less than the specified one are processed by a method working with variable-length fields using the ideas of genetic algorithms: mutations are selected iteratively for a set of proposed boundaries, a quality metric is calculated for each mutation, the best mutations are transferred to the next step.

AB - The article describes a method for restoring the structure of network traffic with zero prior knowledge. The importance of the problem being solved is explained (government authorities requirements and recent incidents in the field of information security). A brief description of the existing approaches is given. The general architecture of the proposed method based on the previous research of the authors is described [5]. Incoming packets are divided into groups according to the format of the transmitted data, for each group a prediction is made of the presence of a field boundary for each offset inside the packet. Groups of packets with a prediction confidence value less than the specified one are processed by a method working with variable-length fields using the ideas of genetic algorithms: mutations are selected iteratively for a set of proposed boundaries, a quality metric is calculated for each mutation, the best mutations are transferred to the next step.

UR - http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85164976245

U2 - 10.1109/USBEREIT58508.2023.10158856

DO - 10.1109/USBEREIT58508.2023.10158856

M3 - Conference contribution

SP - 324

EP - 327

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: 41989256