Evaluating Header Information Features for Malware Infection Detection

• Item type: Journal(1)
• 公開日: 2015-09-15
• タイトル: Evaluating Header Information Features for Malware Infection Detection
• タイトル / 言語: en
• タイトル: Evaluating Header Information Features for Malware Infection Detection
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [特集：社会に浸透していくコンピュータセキュリティ技術] malware, infection detection, traffic, header, vector quantization
• 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: The University of Electro-Communications
• 著者所属: Waseda University
• 著者所属: The University of Electro-Communications
• 著者所属: NTT Communications Corporation
• 著者所属: The University of Electro-Communications
• 著者所属(英): en
• 著者所属(英): The University of Electro-Communications
• 著者所属(英): en
• 著者所属(英): Waseda University
• 著者所属(英): en
• 著者所属(英): The University of Electro-Communications
• 著者所属(英): en
• 著者所属(英): NTT Communications Corporation
• 著者所属(英): en
• 著者所属(英): The University of Electro-Communications
• 著者名: Masatsugu, Ichino; Kenji, Kawamoto; Toru, Iwano; Mitsuhiro, Hatada; Hiroshi, Yoshiura
• 著者名(英): Masatsugu, Ichino; Kenji, Kawamoto; Toru, Iwano; Mitsuhiro, Hatada; Hiroshi, Yoshiura
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: We analyzed traffic data after a malware infection and clarified which features would be the most effective in the detection of infection. The focus is on the use of traffic data to detect infections and on the use of features that do not change much over time from those of the training data. The characteristics of features that are effective for detecting malware infections are also described. Experimental results clarified the effects of the time difference, and the effective features that were little affected by the time difference were identified. There is thus a need to focus on the effect of the time difference when investigating malware infection detection.; \n------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.23(2015) No.5 (online); DOI http://dx.doi.org/10.2197/ipsjjip.23.603; ------------------------------
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: We analyzed traffic data after a malware infection and clarified which features would be the most effective in the detection of infection. The focus is on the use of traffic data to detect infections and on the use of features that do not change much over time from those of the training data. The characteristics of features that are effective for detecting malware infections are also described. Experimental results clarified the effects of the time difference, and the effective features that were little affected by the time difference were identified. There is thus a need to focus on the effect of the time difference when investigating malware infection detection.; \n------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.23(2015) No.5 (online); DOI http://dx.doi.org/10.2197/ipsjjip.23.603; ------------------------------
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00116647
• 書誌情報: 情報処理学会論文誌; 巻 56, 号 9, 発行日 2015-09-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7764