{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00214494","sets":["6164:6165:6462:10749"]},"path":["10749"],"owner":"44499","recid":"214494","title":["IoTマルウェアの分類方法に関する検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-10-19"},"_buckets":{"deposit":"c32d9432-b0e6-4502-ae41-08c6dc18ed04"},"_deposit":{"id":"214494","pid":{"type":"depid","value":"214494","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"IoTマルウェアの分類方法に関する検討","author_link":["550961","550962","550963","550968","550967","550971","550966","550969","550970","550972","550965","550964"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"IoTマルウェアの分類方法に関する検討"},{"subitem_title":"N/A","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"IoTマルウェア，分類，クラスタリング，可視化，YARA 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University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information and Science, Osaka University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information and Science, Osaka 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/214494/files/IPSJCSS2021094.pdf","label":"IPSJCSS2021094.pdf"},"date":[{"dateType":"Available","dateValue":"2023-10-19"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJCSS2021094.pdf","filesize":[{"value":"602.6 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尚"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"猿渡, 俊介"}],"nameIdentifiers":[{}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yutaro, Osako","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Toshihiro, Yamauchi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Katsunari, Yoshioka","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takuya, Fujihashi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takashi, Watanabe","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Shunsuke, Saruwatari","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":"モノがネットワークに接続されることが一般的となり，我々の生活が便利になった．しかしながら，ネットワーク接続されたモノは攻撃者の標的となり，大規模な攻撃への温床となっているため，マルウェアへの対応が必須である．IoT デバイス向けのマルウェアへの対策は，攻撃方法の高速な分析と多様な CPU アーキテクチャへの対応が求められる．このような観点から，本稿では IoT デバイス向けのマルウェアのクラスタリング手法「String-based Malware Clustering Algorithm (SMCA)」を提案する．SMCA では，マルウェアから文字列を抽出し，階層的クラスタリングによって分類木を作成する．文字列ベースの手法では，CPU プラットフォームが異なる同種のマルウェアを近くにクラスタリングすることもできる．また，説明変数が文字列であるため，ユーザが解析しやすいという特徴がある．SMCA の有効性を横浜国立大学吉岡研究室の IoT マルウェアデータセットの4000 検体，VirusTotal を用いて評価した結果，異なるプラットフォームでも機能が似ていれば近い距離にクラスタリングされることが分かった．また，解析の過程で 4000 検体の中でとある文字列を含んだ 25 検体を発見し，調べたところ，そのマルウェアのソースコードらしきものにたどり着くことができた．","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"N/A","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"704","bibliographic_titles":[{"bibliographic_title":"コンピュータセキュリティシンポジウム2021論文集"}],"bibliographicPageStart":"697","bibliographicIssueDates":{"bibliographicIssueDate":"2021-10-19","bibliographicIssueDateType":"Issued"}}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":214494,"updated":"2025-01-19T16:36:26.345513+00:00","links":{},"created":"2025-01-19T01:15:18.601771+00:00"}