{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00209564","sets":["1164:6389:10492:10493"]},"path":["10493"],"owner":"44499","recid":"209564","title":["オンライン機械翻訳システムに対するホモグリフ攻撃の脆弱性調査"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-02-22"},"_buckets":{"deposit":"e0121183-ef1f-4753-925c-98ee272160c3"},"_deposit":{"id":"209564","pid":{"type":"depid","value":"209564","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"オンライン機械翻訳システムに対するホモグリフ攻撃の脆弱性調査","author_link":["528500","528501","528498","528499"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"オンライン機械翻訳システムに対するホモグリフ攻撃の脆弱性調査"},{"subitem_title":"Research on the vulnerability of homoglyph attacks to online machine translation system","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ICSS","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2021-02-22","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"早稲田大学基幹理工学部"},{"subitem_text_value":"早稲田大学基幹理工学部/情報通信研究機構/理化学研究所革新知能統合研究センター"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"School of Fundamental Science and Engineering","subitem_text_language":"en"},{"subitem_text_value":"School of Fundamental Science and Engineering / National Institute of Information and Communications Technology / RIKEN Center for Advanced Intelligence Project","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/209564/files/IPSJ-SPT21041027.pdf","label":"IPSJ-SPT21041027.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SPT21041027.pdf","filesize":[{"value":"1.9 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"46"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"cfb1e9cd-fae0-4406-8755-b46b63d56745","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 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":"坂本, 岳史"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"森, 達哉"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Takeshi, Sakamoto","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tatsuya, Mori","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":"ニューラルネットワークを搭載するシステムには,正当な入力に微小な摂動を加えた悪意ある入力 (Adversarial Input) により,意図的に誤動作が引き起こされるという脆弱性が指摘されている.Adversarial Input は,元の入力との違いが人間には認知されないという特徴をもつ.本研究では,オンラインで利用可能な 8 つの機械翻訳システムに対し,悪意ある入力としてホモグリフや特殊文字を入力した際の出力を調査し,敵対的攻撃に対する脆弱性の評価を行う.調査の結果,各機械翻訳システムに特有の前処理を推定することが可能であるとわかった.本論文では,  前処理の推定結果に基づき,各システムに固有の脆弱性や対策方法について提案する.","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"It has been widely known that systems empowered by neural network algorithms are vulnerable against an intrinsic attack named “Adversarial Input”, which can be generated by adding small perturbations to the original inputs, aiming at fooling the systems. Adversarial Input has the characteristic that the difference from the original input is not recognized by humans. In this research, we investigate the output of eight machine translation systems that can be used online when homoglyphs and special characters are input as malicious inputs, and evaluate their vulnerability to hostile attacks. As a result of the investigation, it was found that it is possible to estimate the preprocessing to each machine translation system. In this paper, we propose vulnerabilities and countermeasures specific to each system based on the estimation results of preprocessing.","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":"2021-02-22","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"27","bibliographicVolumeNumber":"2021-SPT-41"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":209564,"updated":"2025-01-19T18:28:46.574023+00:00","links":{},"created":"2025-01-19T01:10:51.955115+00:00"}