{"updated":"2025-01-20T02:18:40.403974+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00187371","sets":["6164:6165:6462:9463"]},"path":["9463"],"owner":"11","recid":"187371","title":["CNNと注意機構による画像化されたマルウェアの解析手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-10-16"},"_buckets":{"deposit":"4b96f9ea-f4dc-4527-98d2-0a018cefff6f"},"_deposit":{"id":"187371","pid":{"type":"depid","value":"187371","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"CNNと注意機構による画像化されたマルウェアの解析手法","author_link":["423736","423739","423740","423737","423738"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"CNNと注意機構による画像化されたマルウェアの解析手法"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"MWS，マルウェア解析，Convolutional Neural Network，注意機構","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2017-10-16","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":"筑波大学"},{"subitem_text_value":"筑波大学"},{"subitem_text_value":"筑波大学"},{"subitem_text_value":"筑波大学"},{"subitem_text_value":"筑波大学"}]},"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/187371/files/IPSJCSS2017196.pdf","label":"IPSJCSS2017196.pdf"},"date":[{"dateType":"Available","dateValue":"2019-10-16"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJCSS2017196.pdf","filesize":[{"value":"2.8 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"30"},{"tax":["include_tax"],"price":"0","billingrole":"46"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"7e0cbb4b-5656-4d03-bdda-c621453e90d2","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2017 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"矢倉, 大夢"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"篠崎, 慎之介"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"西村, 礼恩"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大山, 恵弘"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"佐久間, 淳"}],"nameIdentifiers":[{}]}]},"item_18_relation_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_select":"NCID","subitem_relation_type_id_text":"ISSN　1882-0840"}}]},"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":"本研究では，画像化されたバイナリデータにCNNを適用することによって，マルウェアからそのファミリに特有の領域を検出する分類手法を提案する．この手法では，CNNに注意機構と呼ばれる仕組みを組み合わせることによって，画像の中で分類に重要な領域を示す「注意度マップ」を出力する．これにより，該当するファミリに特有の領域を検出することでき，人手でその動作を解析する際のヒントとなる．評価実験では，提案手法が既存手法より高い分類精度を誇ることを示すと共に，注意度マップを元にマルウェアを解析することによって，提案手法から得られる情報が，パックされたマルウェアを解析する場合を含め，有用であることを確かめた．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographic_titles":[{"bibliographic_title":"コンピュータセキュリティシンポジウム2017論文集"}],"bibliographicIssueDates":{"bibliographicIssueDate":"2017-10-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"2017"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"created":"2025-01-19T00:54:02.941193+00:00","id":187371,"links":{}}