Presentation 2023-01-19
Flow Classification Using Flow Collections and Deep Learning
Loc Gia Nguyen, Kohei Watabe,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) This study aims to explore the possibility of using collections of flows to improve classification accuracy of network flow data. The proposal uses machine learning techniques, which is effective for modeling of data. Initial empirical results show that the proposed approach has improved classification accuracy compared to previous approaches. The proposed method provides a new methodology for building classification systems.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Network / IDS / BERT / Flow-based / Machine learning
Paper # IN2022-53
Date of Issue 2023-01-12 (IN)

Conference Information
Committee IN
Conference Date 2023/1/19(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Aichi Industry & Labor Center
Topics (in Japanese) (See Japanese page)
Topics (in English) Contents Distribution, Social Networking Services, Data Analytics and Processing Platform, Big data, etc.
Chair Kunio Hato(Internet Multifeed)
Vice Chair Tsutomu Murase(Nagoya Univ.)
Secretary Tsutomu Murase(KDDI Research)
Assistant

Paper Information
Registration To Technical Committee on Information Networks
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Flow Classification Using Flow Collections and Deep Learning
Sub Title (in English)
Keyword(1) Network
Keyword(2) IDS
Keyword(3) BERT
Keyword(4) Flow-based
Keyword(5) Machine learning
1st Author's Name Loc Gia Nguyen
1st Author's Affiliation Nagaoka University of Technology(Nagaoka Univ. of Tech.)
2nd Author's Name Kohei Watabe
2nd Author's Affiliation Nagaoka University of Technology(Nagaoka Univ. of Tech.)
Date 2023-01-19
Paper # IN2022-53
Volume (vol) vol.122
Number (no) IN-342
Page pp.pp.7-12(IN),
#Pages 6
Date of Issue 2023-01-12 (IN)