Instant Messaging Application Traffic Recognition

Pu Wang; Xinrun Lyu; Xiangzhan Yu; Chong Zhang

doi:10.1007/978-3-030-78618-2_60

Instant Messaging Application Traffic Recognition

Pu Wang
, Xinrun Lyu
, Xiangzhan Yu
, Chong Zhang^*

^*Corresponding author for this work

Harbin Institute of Technology
National Computer Network Emergency Response Technical Team/Coordination Center of China

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

Abstract

As a basic work of network security, network traffic recognition plays an important role in network resource management and abnormal network traffic monitoring. At present, network traffic identification has become one of the hottest issues in academic research. In the past research, network traffic analysis was mainly done by Port Matching, Deep Packet Inspection. However, these methods are not perfect, and they are not suitable for today. This paper implements a traffic recognition method based on deep learning and machine learning. Besides, this paper implements unsupervised clustering of traffic. On the UNB ISCX data set, the experimental results are quite good.

Original language	English
Title of host publication	Advances in Artificial Intelligence and Security - 7th International Conference, ICAIS 2021, Proceedings
Editors	Xingming Sun, Xiaorui Zhang, Zhihua Xia, Elisa Bertino
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	727-738
Number of pages	12
ISBN (Print)	9783030786175
DOIs	https://doi.org/10.1007/978-3-030-78618-2_60
State	Published - 2021
Externally published	Yes
Event	7th International Conference on Artificial Intelligence and Security, ICAIS 2021 - Dublin, Ireland Duration: 19 Jul 2021 → 23 Jul 2021

Publication series

Name	Communications in Computer and Information Science
Volume	1423
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	7th International Conference on Artificial Intelligence and Security, ICAIS 2021
Country/Territory	Ireland
City	Dublin
Period	19/07/21 → 23/07/21

Keywords

Deep learning
Machine learning
Network traffic recognition
Unsupervised clustering

Access to Document

10.1007/978-3-030-78618-2_60

Cite this

Wang, P., Lyu, X., Yu, X., & Zhang, C. (2021). Instant Messaging Application Traffic Recognition. In X. Sun, X. Zhang, Z. Xia, & E. Bertino (Eds.), Advances in Artificial Intelligence and Security - 7th International Conference, ICAIS 2021, Proceedings (pp. 727-738). (Communications in Computer and Information Science; Vol. 1423). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-78618-2_60

Wang, Pu ; Lyu, Xinrun ; Yu, Xiangzhan et al. / Instant Messaging Application Traffic Recognition. Advances in Artificial Intelligence and Security - 7th International Conference, ICAIS 2021, Proceedings. editor / Xingming Sun ; Xiaorui Zhang ; Zhihua Xia ; Elisa Bertino. Springer Science and Business Media Deutschland GmbH, 2021. pp. 727-738 (Communications in Computer and Information Science).

@inproceedings{5374413613304a849436e84db41a6846,

title = "Instant Messaging Application Traffic Recognition",

abstract = "As a basic work of network security, network traffic recognition plays an important role in network resource management and abnormal network traffic monitoring. At present, network traffic identification has become one of the hottest issues in academic research. In the past research, network traffic analysis was mainly done by Port Matching, Deep Packet Inspection. However, these methods are not perfect, and they are not suitable for today. This paper implements a traffic recognition method based on deep learning and machine learning. Besides, this paper implements unsupervised clustering of traffic. On the UNB ISCX data set, the experimental results are quite good.",

keywords = "Deep learning, Machine learning, Network traffic recognition, Unsupervised clustering",

author = "Pu Wang and Xinrun Lyu and Xiangzhan Yu and Chong Zhang",

note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 7th International Conference on Artificial Intelligence and Security, ICAIS 2021 ; Conference date: 19-07-2021 Through 23-07-2021",

year = "2021",

doi = "10.1007/978-3-030-78618-2\_60",

language = "英语",

isbn = "9783030786175",

series = "Communications in Computer and Information Science",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "727--738",

editor = "Xingming Sun and Xiaorui Zhang and Zhihua Xia and Elisa Bertino",

booktitle = "Advances in Artificial Intelligence and Security - 7th International Conference, ICAIS 2021, Proceedings",

address = "德国",

}

Wang, P, Lyu, X, Yu, X & Zhang, C 2021, Instant Messaging Application Traffic Recognition. in X Sun, X Zhang, Z Xia & E Bertino (eds), Advances in Artificial Intelligence and Security - 7th International Conference, ICAIS 2021, Proceedings. Communications in Computer and Information Science, vol. 1423, Springer Science and Business Media Deutschland GmbH, pp. 727-738, 7th International Conference on Artificial Intelligence and Security, ICAIS 2021, Dublin, Ireland, 19/07/21. https://doi.org/10.1007/978-3-030-78618-2_60

Instant Messaging Application Traffic Recognition. / Wang, Pu; Lyu, Xinrun; Yu, Xiangzhan et al.
Advances in Artificial Intelligence and Security - 7th International Conference, ICAIS 2021, Proceedings. ed. / Xingming Sun; Xiaorui Zhang; Zhihua Xia; Elisa Bertino. Springer Science and Business Media Deutschland GmbH, 2021. p. 727-738 (Communications in Computer and Information Science; Vol. 1423).

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

TY - GEN

T1 - Instant Messaging Application Traffic Recognition

AU - Wang, Pu

AU - Lyu, Xinrun

AU - Yu, Xiangzhan

AU - Zhang, Chong

PY - 2021

Y1 - 2021

N2 - As a basic work of network security, network traffic recognition plays an important role in network resource management and abnormal network traffic monitoring. At present, network traffic identification has become one of the hottest issues in academic research. In the past research, network traffic analysis was mainly done by Port Matching, Deep Packet Inspection. However, these methods are not perfect, and they are not suitable for today. This paper implements a traffic recognition method based on deep learning and machine learning. Besides, this paper implements unsupervised clustering of traffic. On the UNB ISCX data set, the experimental results are quite good.

AB - As a basic work of network security, network traffic recognition plays an important role in network resource management and abnormal network traffic monitoring. At present, network traffic identification has become one of the hottest issues in academic research. In the past research, network traffic analysis was mainly done by Port Matching, Deep Packet Inspection. However, these methods are not perfect, and they are not suitable for today. This paper implements a traffic recognition method based on deep learning and machine learning. Besides, this paper implements unsupervised clustering of traffic. On the UNB ISCX data set, the experimental results are quite good.

KW - Deep learning

KW - Machine learning

KW - Network traffic recognition

KW - Unsupervised clustering

UR - https://www.scopus.com/pages/publications/85111974585

U2 - 10.1007/978-3-030-78618-2_60

DO - 10.1007/978-3-030-78618-2_60

M3 - 会议稿件

AN - SCOPUS:85111974585

SN - 9783030786175

T3 - Communications in Computer and Information Science

SP - 727

EP - 738

BT - Advances in Artificial Intelligence and Security - 7th International Conference, ICAIS 2021, Proceedings

A2 - Sun, Xingming

A2 - Zhang, Xiaorui

A2 - Xia, Zhihua

A2 - Bertino, Elisa

PB - Springer Science and Business Media Deutschland GmbH

T2 - 7th International Conference on Artificial Intelligence and Security, ICAIS 2021

Y2 - 19 July 2021 through 23 July 2021

ER -

Wang P, Lyu X, Yu X, Zhang C. Instant Messaging Application Traffic Recognition. In Sun X, Zhang X, Xia Z, Bertino E, editors, Advances in Artificial Intelligence and Security - 7th International Conference, ICAIS 2021, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 727-738. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-78618-2_60

Instant Messaging Application Traffic Recognition

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