{"updated":"2025-01-19T11:45:20.096549+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00228704","sets":["6164:6165:6462:11379"]},"path":["11379"],"owner":"44499","recid":"228704","title":["生成電力波形によるIoT異常動作検知手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-10-23"},"_buckets":{"deposit":"a9bc15b4-3fce-4a88-82dd-84095c33608d"},"_deposit":{"id":"228704","pid":{"type":"depid","value":"228704","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"生成電力波形によるIoT異常動作検知手法","author_link":["613379","613380","613382","613381"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"生成電力波形によるIoT異常動作検知手法"},{"subitem_title":"Detection of IoT Anomalous Behavior Using Power Analysis","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"生成電力波形，生成モデル，異常動作検知，サイドチャネル解析，電力解析，IoTデバイス","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2023-10-23","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":"早稲田大学基幹理工学研究科情報理工・情報通信専攻"},{"subitem_text_value":"早稲田大学基幹理工学研究科情報理工・情報通信専攻"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Dept. Computer Science and Communications Engineering, Waseda University","subitem_text_language":"en"},{"subitem_text_value":"Dept. Computer Science and Communications Engineering, Waseda University\n","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/228704/files/IPSJ-CSS2023091.pdf","label":"IPSJ-CSS2023091.pdf"},"date":[{"dateType":"Available","dateValue":"2025-10-23"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CSS2023091.pdf","filesize":[{"value":"2.2 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":"f03ee3f5-ff4c-40b5-93b3-3b507cae43bc","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"久古, 幸汰"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"戸川, 望"}],"nameIdentifiers":[{}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Kota, Hisafuru","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Nozomu, Togawa","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":"近年，Internet of Things (IoT) デバイスの普及に伴い，サプライチェーン上に第三者が介入する機会が増加し，IoT デバイスのセキュリティ課題が顕在化している．電力解析により IoT デバイスの異常動作を検知する手法が知られているが，IoT デバイスは OS やハードウェア自体が電力を消費し定常的に電力を消費するため，異常動作検知にはこのような定常的な電力を除去する必要がある．従来，異常動作検知では，定常状態の電力を手動で除去しており，また電力波形の特定の特徴から異常動作を検知していたため，十分に異常動作を検知できない場合があった．本稿では，機械学習により定常状態の位置を推定することでアプリケーション電力波形を生成し，その波形から潜在的な特徴量を抽出することで自動的に異常動作を検知する手法を提案する．実験の結果，従来の IoT 異常動作検知手法では検知出来なかった電力波形に対し，提案手法を適用することで異常動作の検知に成功した．","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In this paper, we propose an anomalous behavior detection method in Internet-of-Things devices by analyzing power consumption. Experimental evaluations show that the proposed method detects anomalous application behaviors successfully, while the recent state-of-the-art method cannot detect them.","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"675","bibliographic_titles":[{"bibliographic_title":"コンピュータセキュリティシンポジウム2023論文集"}],"bibliographicPageStart":"668","bibliographicIssueDates":{"bibliographicIssueDate":"2023-10-23","bibliographicIssueDateType":"Issued"}}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:27:50.703376+00:00","id":228704,"links":{}}