多 変量 解析 による標的 型 攻撃 の分類
書誌 事項
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タイトル
別名 -
- Using Multivariate Statistics to Classify Targeted Attacks
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抄録
Targeted attacks that exploit confidential information or personal information are serious threats for many organizations. Recently, attackers use the infected terminals as stepping stones, and often change destination of the stolen information. Thus, it is difficult to identify and reveal the true attacker. To identify the true attacker, we need to analyze commonality between targeted attacks and classify the attacks under each attacker. However, it is not clear which parameters indicate characteristic of attackers most, and not easy to classify the attacks under each attacker. In this paper, we use principal component analysis to investigate a tendency of targeted attacks. Next, we use factor analysis to find the factors that indicate characteristic of targeted attacks, and select high correlation parameters between an attacker. Furthermore, we determine priority of parameters by computing the corresponding factor loadings and use cluster analysis to assign a set of attacks into attackers.
収録 刊行 物
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情報処理 学会 論文 誌 -
情報処理 学会 論文 誌 54 (12), 2461-2471, 2013-12-15
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詳細 情報 詳細 情報 について
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- CRID
- 1050564287857773056
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- NII
論文 ID - 110009646891
- NII
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- NII
書誌 ID - AN00116647
- NII
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- ISSN
- 18827764
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- Web Site
- http://id.nii.ac.jp/1001/00096742/
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本文 言語 コード- ja
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資料 種別 - journal article
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- データソース
種別 -
- IRDB
- CiNii Articles
- KAKEN
- データソース