{"created":"2025-01-19T01:28:00.934872+00:00","updated":"2025-01-19T11:41:03.931790+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00228882","sets":["1164:2036:11089:11372"]},"path":["11372"],"owner":"44499","recid":"228882","title":["入力デコーダを使用したMTJ-PUFの提案と機械学習耐性の評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-11-10"},"_buckets":{"deposit":"d95c3687-7bdf-4bf0-b9d1-b60a9b0a1399"},"_deposit":{"id":"228882","pid":{"type":"depid","value":"228882","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"入力デコーダを使用したMTJ-PUFの提案と機械学習耐性の評価","author_link":["614505","614506","614504","614503"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"入力デコーダを使用したMTJ-PUFの提案と機械学習耐性の評価"},{"subitem_title":"MTJ-PUF with Input Decoder and Evaluation of Machine Learning Resistance","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"VLSI設計技術 ","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2023-11-10","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"芝浦工業大学大学院理工学研究科"},{"subitem_text_value":"芝浦工業大学大学院理工学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Shibaura Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Shibaura Institute of Technology","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/228882/files/IPSJ-SLDM23204015.pdf","label":"IPSJ-SLDM23204015.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SLDM23204015.pdf","filesize":[{"value":"1.9 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"10"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"0fc914a1-03de-41f3-a9b0-22d5a11b9435","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"菊地, 拓"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"宇佐美, 公良"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Takumi, Kikuchi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kimiyoshi, Usami","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11451459","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8639","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"LSI の個体認証技術の 1 つである PUF (Physically Unclonable Function) は，機械学習 (ML) を用いたモデリング攻撃による脆弱性の問題がある．本稿では，モデリング攻撃に対する耐性を向上させるために，製造時に生じる MTJ (Magnetic Tunnel Junction) のばらつきを使用した，入力デコーダ型 MTJ-PUF を提案する．提案した MTJ- PUF に対して，多層パーセプトロン (MLP)，線形回帰 (LR)，サポートベクターマシン (SVM) を用いたモデリング攻撃を行い脆弱性を評価した結果，それぞれの予測精度は理想値である 50% に近い値であり，提案する入力デコーダ型 MTJ-PUF は ML 攻撃に耐性があることが示された．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Physically Unclonable Function (PUF), one of the LSI individual authentication techniques, is vulnerable to machine learning (ML) modeling attacks. In this paper, we propose an input-decoder type MTJ-PUF that uses the variation of MTJ (Magnetic Tunnel Junction) during manufacturing to improve the resistance against modeling attacks. We evaluated the vulnerability of the proposed MTJ-PUF to modeling attacks using the multilayer perceptron (MLP), linear regression (LR), and support vector machine (SVM). Results demonstrated that the prediction accuracy of each modeling attack is close to the ideal value of 50%, indicating that the proposed input decoder MTJ-PUF is resistant to ML attack.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告システムとLSIの設計技術（SLDM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2023-11-10","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"15","bibliographicVolumeNumber":"2023-SLDM-204"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":228882,"links":{}}