Presentation 2018-07-12
Attack classification method using neural network by analysis of log data of intrusion detection system and investigation for improvement of accuracy
Tsukasa Mannen, Kohei Shiomoto,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In this paper, we focus on the Intrusion Detection System (IDS) and examine the accuracy of attack and non-attack classifications through the Neural network. For the high accuracy we used the Batch Normalization and fond that utility. Additionally, we analyzed the differences of attack’s feature.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Machine learning / KDD cup 99 Data / Neural network / Batch Normalization
Paper # SR2018-31
Date of Issue 2018-07-04 (SR)

Conference Information
Committee ASN / NS / RCS / SR / RCC
Conference Date 2018/7/11(3days)
Place (in Japanese) (See Japanese page)
Place (in English) Hakodate Arena
Topics (in Japanese) (See Japanese page)
Topics (in English) Wireless Distributed Network, Machine Learning and AI for Wireless Communications and Networks, M2M (Machine-to-Machine), D2D (Device-to-Device), IoT(Internet of Things), etc.
Chair Hiraku Okada(Nagoya Univ.) / Yoshikatsu Okazaki(NTT) / Tomoaki Otsuki(Keio Univ.) / Kenta Umebayashi(Tokyo Univ. of Agric. and Tech.) / Kazunori Hayashi(Osaka City Univ.)
Vice Chair Koji Yamamoto(Kyoto Univ.) / Jin Nakazawa(Keio Univ.) / Kazuya Monden(Hitachi) / Akihiro Nakao(Univ. of Tokyo) / Eisuke Fukuda(Fujitsu Labs.) / Satoshi Suyama(NTT DoCoMo) / Fumiaki Maehara(Waseda Univ.) / Masayuki Ariyoshi(NEC) / Suguru Kameda(Tohoku Univ.) / Shunichi Azuma(Nagoya Univ.) / HUAN-BANG LI(NICT)
Secretary Koji Yamamoto(NICT) / Jin Nakazawa(Sophia Univ.) / Kazuya Monden(Kanagawa Inst. of Tech.) / Akihiro Nakao(NTT) / Eisuke Fukuda(Osaka Pref Univ.) / Satoshi Suyama(Hokkaido Univ.) / Fumiaki Maehara(NTT) / Masayuki Ariyoshi(NICT) / Suguru Kameda(ATR) / Shunichi Azuma(Univ. of Electro-Comm.) / HUAN-BANG LI(Kagawa Univ.)
Assistant Masafumi Hashimoto(Osaka Univ.) / Tomoyuki Ota(Hiroshima City Univ.) / Tatsuya Kikuzuki(Fujitu Lab.) / Ryo Nakano(HITACHI) / Yoshifumi Hotta(Mitsubishi Electric) / Kenichi Kashibuchi(NTT) / Kazushi Muraoka(NTT DOCOMO) / Shinsuke Ibi(Osaka Univ.) / Hiroshi Nishimoto(Mitsubishi Electric) / Koichi Adachi(Univ. of Electro-Comm.) / Osamu Nakamura(Sharp) / Gia Khanh Tran(Tokyo Inst. of Tech.) / Syusuke Narieda(Mie Univ.) / Koji Ohshima(Kozo Keikaku Engineering) / Mai Ohta(Fukuoka Univ.) / Teppei Oyama(Fujitsu Lab.) / Toshinori Kagawa(NICT) / Masateru Ogura(NAIST)

Paper Information
Registration To Technical Committee on Ambient intelligence and Sensor Networks / Technical Committee on Network Systems / Technical Committee on Radio Communication Systems / Technical Committee on Smart Radio / Technical Committee on Reliable Communication and Control
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Attack classification method using neural network by analysis of log data of intrusion detection system and investigation for improvement of accuracy
Sub Title (in English)
Keyword(1) Machine learning
Keyword(2) KDD cup 99 Data
Keyword(3) Neural network
Keyword(4) Batch Normalization
1st Author's Name Tsukasa Mannen
1st Author's Affiliation Tokyo City University(TCU)
2nd Author's Name Kohei Shiomoto
2nd Author's Affiliation Tokyo City University(TCU)
Date 2018-07-12
Paper # SR2018-31
Volume (vol) vol.118
Number (no) SR-126
Page pp.pp.65-72(SR),
#Pages 8
Date of Issue 2018-07-04 (SR)