Presentation 2018-05-17
Data Analytics for Early Detection of Anomalies in Campus Networks
Shingo Ata,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Recently, automation of operations and management of ICT infrastructure, including information systems and networking, is much attracted. To apply appropriate operations, it is important to forecast a behavior of users, terminals, and networks by combining various types of log data from servers or networking devices. Especially, to catch behaviors with high accuracy is dominant for avoiding incorrect operations, however, it is still unclear what kind of log data, and/or what kind of methods are effective to achieve accurate identification. In this paper, we present a current status of capturing log data and their analysis in our campus network, and discuss issues for early detection of anomalies.
Keyword(in Japanese) (See Japanese page)
Keyword(in English)
Paper # ICM2018-4
Date of Issue 2018-05-10 (ICM)

Conference Information
Committee ICM / IPSJ-CSEC / IPSJ-IOT
Conference Date 2018/5/17(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
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Topics (in English)
Chair Kiyohito Yoshihara(KDDI Research)
Vice Chair Yoichi Yamashita(NTT Neomeit) / Takumi Miyoshi(Shibaura Inst. Tech.)
Secretary Yoichi Yamashita(KDDI Research) / Takumi Miyoshi(NTT)
Assistant Yuncheng Zhu(Hitachi)

Paper Information
Registration To Technical Committee on Information and Communication Management / Special Interest Group on Computer Security / Special Interest Group on Internet and Operation Technology
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Data Analytics for Early Detection of Anomalies in Campus Networks
Sub Title (in English)
Keyword(1)
1st Author's Name Shingo Ata
1st Author's Affiliation Osaka City University(Osaka City Univ.)
Date 2018-05-17
Paper # ICM2018-4
Volume (vol) vol.118
Number (no) ICM-39
Page pp.pp.39-44(ICM),
#Pages 6
Date of Issue 2018-05-10 (ICM)