{"updated":"2025-01-21T20:44:21.478588+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00078030","sets":["6164:6165:6462:6551"]},"path":["6551"],"owner":"10","recid":"78030","title":["APIの傾向によるラベル付けとSVMによるマルウェアの分類"],"pubdate":{"attribute_name":"公開日","attribute_value":"2011-10-12"},"_buckets":{"deposit":"284a707a-47e4-4001-8a34-94e3477996c9"},"_deposit":{"id":"78030","pid":{"type":"depid","value":"78030","revision_id":0},"owners":[10],"status":"published","created_by":10},"item_title":"APIの傾向によるラベル付けとSVMによるマルウェアの分類","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"APIの傾向によるラベル付けとSVMによるマルウェアの分類"},{"subitem_title":"Malware Classification based on SVM and Labeling by API's Tendency","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"コンピュータウィルス（２）","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2011-10-12","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"慶應義塾大学環境情報学部"},{"subitem_text_value":"慶應義塾大学大学院政策・メディア研究科"},{"subitem_text_value":"慶應義塾大学環境情報学部"},{"subitem_text_value":"慶應義塾大学環境情報学部"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Faculty of Environment and Information Studies, Keio University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Media and Governance, Keio University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Environment and Information Studies, Keio University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Environment and Information Studies, Keio University","subitem_text_language":"en"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/78030/files/IPSJCSS2011135.pdf"},"date":[{"dateType":"Available","dateValue":"2012-10-12"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJCSS2011135.pdf","filesize":[{"value":"282.4 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"44"},{"tax":["include_tax"],"price":"30000","billingrole":"5"}],"accessrole":"open_date","version_id":"d5374763-8a85-4645-9f15-2ebd6605cbc3","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2011 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"碓井, 利宣"},{"creatorName":"重松, 邦彦"},{"creatorName":"武田, 圭史"},{"creatorName":"村井, 純"}],"nameIdentifiers":[{}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Toshinori, Usui","creatorNameLang":"en"},{"creatorName":"Kunihiko, Shigematsu","creatorNameLang":"en"},{"creatorName":"Keiji, Takeda","creatorNameLang":"en"},{"creatorName":"Jun, Murai","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"インターネット利用の普及に伴い，様々な悪意を持った新たなマルウェアが日々出現しており，これらについて効果的な対応を効率よく実施するためには，発見されたマルウェアを短時間で分析する必要がある．本研究では，静的解析手法を用いてマルウェアの挙動に関する情報を抽出し，そこで利用されるAPIの傾向によってラベル付けを行う．それらの情報を基にして機械学習であるSupport Vector Machineにより分類する．本手法によって特に挙動の類似性の高いマルウェア同士を同じグループとして分類するシステムを実装した．本システムを用いることで，分析者は分類結果から挙動の傾向を短時間で把握することができ亜種の特定や対策の立案などに活用できる．","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"With the spread of the internet, various kinds of new malwares have appeared. Therefore, to take effective measures to cope with these efficiently, we need to analyze malwares in fast method. In our proposing method, we extract information which is related to malwares' behavior by static analysis, affix labels to malwares based on its APIs' tendency, and classificate them by Support Vector Machine. We implemented automatic classification system according to our method. By using our system, analysts can know malwares' behavior easily from the result of the classification.","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"802","bibliographic_titles":[{"bibliographic_title":"コンピュータセキュリティシンポジウム2011 論文集"}],"bibliographicPageStart":"797","bibliographicIssueDates":{"bibliographicIssueDate":"2011-10-12","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"3","bibliographicVolumeNumber":"2011"}]},"relation_version_is_last":true,"weko_creator_id":"10"},"created":"2025-01-18T23:33:29.605862+00:00","id":78030,"links":{}}