{"links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00237171","sets":["1164:6389:11481:11662"]},"path":["11662"],"owner":"44499","recid":"237171","title":["物理乱数を用いたDenoising Auto EncoderによるAdversarial Examples攻撃への防御性能に関する検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-07-15"},"_buckets":{"deposit":"921202e3-44d9-4849-ac26-ca1254d0e99a"},"_deposit":{"id":"237171","pid":{"type":"depid","value":"237171","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"物理乱数を用いたDenoising Auto EncoderによるAdversarial Examples攻撃への防御性能に関する検討","author_link":["648721","648714","648716","648719","648713","648720","648718","648717","648712","648715"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"物理乱数を用いたDenoising Auto EncoderによるAdversarial Examples攻撃への防御性能に関する検討"},{"subitem_title":"Defending Against Adversarial Example Attacks by a Denoising Autoencoder and Physical Random Noise","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"HWS/ICSS","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-07-15","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"立命館大学理工学研究科"},{"subitem_text_value":"立命館大学理工学研究科"},{"subitem_text_value":"立命館大学理工学研究科"},{"subitem_text_value":"立命館大学理工学研究科"},{"subitem_text_value":"立命館大学理工学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Research Organization of Science and Engineering Ritsumeikan University","subitem_text_language":"en"},{"subitem_text_value":"Research Organization of Science and Engineering Ritsumeikan University","subitem_text_language":"en"},{"subitem_text_value":"Research Organization of Science and Engineering Ritsumeikan University","subitem_text_language":"en"},{"subitem_text_value":"Research Organization of Science and Engineering Ritsumeikan University","subitem_text_language":"en"},{"subitem_text_value":"Research Organization of Science and Engineering Ritsumeikan University","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/237171/files/IPSJ-SPT24056050.pdf","label":"IPSJ-SPT24056050.pdf"},"date":[{"dateType":"Available","dateValue":"2026-07-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SPT24056050.pdf","filesize":[{"value":"2.2 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俊介"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yuki, Rogi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kota, Yoshida","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tatsuya, Oyama","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takeshi, Fujino","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Shunsuke, Okura","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12628305","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":"2188-8671","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"IoT (Internet of Things) ですべての人とモノがつながり，様々な知識や情報が共有され，今までにない新たな価値を生み出すことが期待されている．フィジカル空間のセンサからの膨大な情報はサイバー空間に蓄積され，このビックデータを  AI が解析し，解析結果がフィジカル空間に様々な形でフィードバックされる．ここで，プライバシー保護やリアルタイム応答のために，フィジカル空間に配置したエッジデバイス内でセンサからの情報を処理するエッジ AI が注目されている．エッジ AI への攻撃の一つとして，CNN (Convolutional Neural Network) への入力に対して微小なノイズ (摂動) を付加することで，作為的に誤認識を引き起こす AEs (Adversarial Examples) 攻撃がある．エッジ AI に対する AEs 攻撃に対する 1 つの解決策として，摂動攪乱ノイズを付加してから DAE (Denoising Autoencoder) を用いることによって敵対的摂動を取り除く防御手法が提案されている．本稿では，まず，予測可能な疑似乱数ノイズを利用した場合，摂動攪乱ノイズを利用する防御手法の有効性が低いことを示す．次に，イメージセンサで生成される熱雑音に基づく予測不可能なノイズを利用する防御手法と，熱雑音用の前処理手法を提案する．イメージセンサの熱雑音を測定し,前処理により生成した摂動攪乱ノイズを NIST 800-22 乱数検定で評価した結果，全ての項目が合格し，高いランダム性を持つことを確認した．NIST 800-90B 乱数検定で評価した結果，イメージセンサに起因する熱雑音の Min-Entropy は，0.74 であると推定された．さらに，AEs 攻撃に対する防御性能が 24% 向上することを確認した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告セキュリティ心理学とトラスト（SPT）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-07-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"50","bibliographicVolumeNumber":"2024-SPT-56"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:39:39.047459+00:00","updated":"2025-01-19T08:58:17.786435+00:00","id":237171}