{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00232722","sets":["1164:4619:11539:11552"]},"path":["11552"],"owner":"44499","recid":"232722","title":["人間と機械学習モデルの両者をだますAdversarial Example の作成方法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-02-25"},"_buckets":{"deposit":"66b75d32-a99d-4e90-b7c1-a514a0b59d3b"},"_deposit":{"id":"232722","pid":{"type":"depid","value":"232722","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"人間と機械学習モデルの両者をだますAdversarial Example の作成方法","author_link":["630675","630682","630681","630679","630674","630676","630680","630677","630678","630683"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"人間と機械学習モデルの両者をだますAdversarial Example の作成方法"},{"subitem_title":"Creating Adversarial Examples to Deceive Both Humans and Machine Learning Models","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2024-02-25","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"早稲田大学"},{"subitem_text_value":"NTT社会情報研究所"},{"subitem_text_value":"NTTセキュリティホールディングス"},{"subitem_text_value":"NTT社会情報研究所"},{"subitem_text_value":"早稲田大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Waseda University","subitem_text_language":"en"},{"subitem_text_value":"NTT Social Informatics Laboratories","subitem_text_language":"en"},{"subitem_text_value":"NTT Security Holdings","subitem_text_language":"en"},{"subitem_text_value":"NTT Social Informatics Laboratories","subitem_text_language":"en"},{"subitem_text_value":"Waseda 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/232722/files/IPSJ-CVIM24237031.pdf","label":"IPSJ-CVIM24237031.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM24237031.pdf","filesize":[{"value":"1.8 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"955159f9-f737-4cf4-8247-7a4822bb646a","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 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":"藤森, 洸"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"芝原, 俊樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"千葉, 大紀"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"秋山, 満昭"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"内田, 真人"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Ko, Fujimori","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Toshiki, Shibahara","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Daiki, Chiba","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Mitsuaki, Akiyama","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Masato, Uchida","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11131797","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":"2188-8701","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"ニューラルネットワークに対する脆弱性攻撃の一つとして，入力データに微小なノイズを加えることで作為的に誤分類を誘発させる Adversarial Example（AE）がある．AE による「攻撃成功」は，ノイズを人間に認識されることなく機械学習モデルを誤分類させることとして定義される．しかし，AE の攻撃手法に関する既存研究では，機械学習モデルを誤分類させることのみが着目されており，ノイズの視認性について評価していない場合がある．代表的な攻撃手法である Fast Gradient Sign Method が提案された論文で行われた評価実験と同じ条件下で作成された AE は，大多数がノイズを視認できることが確認されている．そこで本研究では，視覚的に自然に見える AE の作成方法を提案する．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"One of the vulnerability attacks against neural networks is the generation of Adversarial Examples (AE), which induce misclassification by adding minimal noise to input data. The “attack success” by AE is defined as causing a machine learning model to misclassify without the noise being recognized by humans. However, existing research on AE attack methods often focuses solely on causing misclassification of machine learning models and may not evaluate the visibility of the noise. Evaluation experiments conducted in the same conditions as the paper that proposed the prominent attack method, the Fast Gradient Sign Method, have confirmed that the majority of AEs are perceptible with noise. Therefore, in this study, we propose a method for creating AEs that appear visually natural.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告コンピュータビジョンとイメージメディア（CVIM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-02-25","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"31","bibliographicVolumeNumber":"2024-CVIM-237"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":232722,"updated":"2025-01-19T10:20:33.191819+00:00","links":{},"created":"2025-01-19T01:33:45.035701+00:00"}