| Item type |
Trans(1) |
| 公開日 |
2016-08-10 |
| タイトル |
|
|
タイトル |
A Semi-Supervised Data Screening for Network Traffic Data Using Graph Min-Cuts |
| タイトル |
|
|
言語 |
en |
|
タイトル |
A Semi-Supervised Data Screening for Network Traffic Data Using Graph Min-Cuts |
| 言語 |
|
|
言語 |
eng |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
[事例紹介論文] semi-supervised learning, minimum cut, data screening, incident detection, darknet monitoring. |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| 著者所属 |
|
|
|
Faculty of International Studies, Kyushu International University／Institute of Systems, Information Technologies and Nanotechnologies (ISIT) |
| 著者所属 |
|
|
|
Institute of Systems, Information Technologies and Nanotechnologies (ISIT)／Department of Informatics, Kyushu University |
| 著者所属 |
|
|
|
Institute of Systems, Information Technologies and Nanotechnologies (ISIT) |
| 著者所属(英) |
|
|
|
en |
|
|
Faculty of International Studies, Kyushu International University / Institute of Systems, Information Technologies and Nanotechnologies (ISIT) |
| 著者所属(英) |
|
|
|
en |
|
|
Institute of Systems, Information Technologies and Nanotechnologies (ISIT) / Department of Informatics, Kyushu University |
| 著者所属(英) |
|
|
|
en |
|
|
Institute of Systems, Information Technologies and Nanotechnologies (ISIT) |
| 著者名 |
Takayoshi, Shoudai
Hikaru, Murai
Atsushi, Okamoto
|
| 著者名(英) |
Takayoshi, Shoudai
Hikaru, Murai
Atsushi, Okamoto
|
| 論文抄録 |
|
|
内容記述タイプ |
Other |
|
内容記述 |
There are currently many projects aimed at devising efficient countermeasures against critical incidents occurring on the Internet through early detection. A nasty problem is hard-to-find accesses by well-analyzed malware whose packets make anomaly detection harder. In this paper, in order to find such accesses from raw data obtained by network monitoring, we propose an automatic data screening method using graph-based semi-supervised learning (Blum and Chawla, 2001) and show its effectiveness in experiments on darknet traffic. |
| 論文抄録(英) |
|
|
内容記述タイプ |
Other |
|
内容記述 |
There are currently many projects aimed at devising efficient countermeasures against critical incidents occurring on the Internet through early detection. A nasty problem is hard-to-find accesses by well-analyzed malware whose packets make anomaly detection harder. In this paper, in order to find such accesses from raw data obtained by network monitoring, we propose an automatic data screening method using graph-based semi-supervised learning (Blum and Chawla, 2001) and show its effectiveness in experiments on darknet traffic. |
| 書誌レコードID |
|
|
収録物識別子タイプ |
NCID |
|
収録物識別子 |
AA11464803 |
| 書誌情報 |
情報処理学会論文誌数理モデル化と応用（TOM）
巻 9,
号 2,
p. 49-60,
発行日 2016-08-10
|
| ISSN |
|
|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
1882-7780 |
| 出版者 |
|
|
言語 |
ja |
|
出版者 |
情報処理学会 |
IPSJ-TOM0902007.pdf (1.4 MB)
