{"created":"2023-06-19T10:30:10.872583+00:00","id":10381,"links":{},"metadata":{"_buckets":{"deposit":"2a864410-950b-461c-b290-e3a6e8fb233d"},"_deposit":{"created_by":18,"id":"10381","owners":[18],"pid":{"revision_id":0,"type":"depid","value":"10381"},"status":"published"},"_oai":{"id":"oai:muroran-it.repo.nii.ac.jp:00010381","sets":["216:316","216:352","46"]},"author_link":["39157","58261","21131","58260","58259"],"item_79_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2020","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"5","bibliographicPageEnd":"3277","bibliographicPageStart":"3267","bibliographicVolumeNumber":"16","bibliographic_titles":[{"bibliographic_title":"IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS","bibliographic_titleLang":"en"}]}]},"item_79_description_23":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_79_description_7":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Individually reinforcing the robustness of a single deep learning model only gives limited security guarantees especially when facing adversarial examples. In this article, we propose DeSVig, a decentralized swift vigilance framework to identify adversarial attacks in an industrial artificial intelligence systems (IAISs), which enables IAISs to correct the mistake in a few seconds. The DeSVig is highly decentralized, which improves the effectiveness of recognizing abnormal inputs. We try to overcome the challenges on ultralow latency caused by dynamics in industries using peculiarly designated mobile edge computing and generative adversarial networks. The most important advantage of our work is that it can significantly reduce the failure risks of being deceived by adversarial examples, which is critical for safety-prioritized and delay-sensitive environments. In our experiments, adversarial examples of industrial electronic components are generated by several classical attacking models. Experimental results demonstrate that the DeSVig is more robust, efficient, and scalable than some state-of-art defenses.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_79_link_17":{"attribute_name":"出版者版へのリンク","attribute_value_mlt":[{"subitem_link_text":"10.1109/TII.2019.2951766","subitem_link_url":"https://doi.org/10.1109/TII.2019.2951766"}]},"item_79_link_5":{"attribute_name":"室蘭工業大学研究者データベースへのリンク","attribute_value_mlt":[{"subitem_link_text":"太田 香（OTA Kaoru）","subitem_link_url":"http://rdsoran.muroran-it.ac.jp/html/100000140_ja.html"},{"subitem_link_text":"董 冕雄（DONG Mianxiong）","subitem_link_url":"http://rdsoran.muroran-it.ac.jp/html/100000145_ja.html"}]},"item_79_publisher_11":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC","subitem_publisher_language":"en"}]},"item_79_relation_18":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type":"isVersionOf","subitem_relation_type_id":{"subitem_relation_type_id_text":"10.1109/TII.2019.2951766","subitem_relation_type_select":"DOI"}}]},"item_79_rights_19":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.","subitem_rights_language":"en"}]},"item_79_source_id_12":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1551-3203","subitem_source_identifier_type":"PISSN"}]},"item_79_subject_9":{"attribute_name":"日本十進分類法","attribute_value_mlt":[{"subitem_subject":"007","subitem_subject_scheme":"NDC"}]},"item_79_version_type_21":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_ab4af688f83e57aa","subitem_version_type":"AM"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_abf2"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"LI, Gaolei","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{}],"affiliationNames":[{},{}]}],"creatorNames":[{"creatorName":"OTA,  Kaoru","creatorNameLang":"en"},{"creatorName":"太田, 香","creatorNameLang":"ja"},{"creatorName":"オオタ, カオル","creatorNameLang":"ja-Kana"}],"familyNames":[{},{},{}],"givenNames":[{},{},{}],"nameIdentifiers":[{},{}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{}],"affiliationNames":[{},{}]}],"creatorNames":[{"creatorName":"DONG,  Mianxiong","creatorNameLang":"en"},{"creatorName":"トウ, メンユウ","creatorNameLang":"ja-Kana"},{"creatorName":"董, 冕雄","creatorNameLang":"ja"}],"familyNames":[{},{},{}],"givenNames":[{},{},{}],"nameIdentifiers":[{},{}]},{"creatorNames":[{"creatorName":"WU, Jun","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"LI, Jianhua","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2020-12-08"}],"displaytype":"detail","filename":"IEEETII_16_5_3267_3277.pdf","filesize":[{"value":"1.1 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"IEEETII_16_5_3267_3277","objectType":"fulltext","url":"https://muroran-it.repo.nii.ac.jp/record/10381/files/IEEETII_16_5_3267_3277.pdf"},"version_id":"dbb4e5c1-0018-450a-a44e-16f17d86107a"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Deep learning","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Computational modeling","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Edge computing","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Data models","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Informatics","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Robustness","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"5G mobile communication","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Adversarial examples","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"deep learning","subitem_subject_scheme":"Other"},{"subitem_subject":"generative adversarial networks (GAN)","subitem_subject_scheme":"Other"},{"subitem_subject":"industrial artificial intelligence systems (IAISs)","subitem_subject_scheme":"Other"},{"subitem_subject":"mobile edge computing","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"DeSVig: Decentralized Swift Vigilance Against Adversarial Attacks in Industrial Artificial Intelligence Systems","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"DeSVig: Decentralized Swift Vigilance Against Adversarial Attacks in Industrial Artificial Intelligence Systems","subitem_title_language":"en"}]},"item_type_id":"79","owner":"18","path":["46","316","352"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2020-12-08"},"publish_date":"2020-12-08","publish_status":"0","recid":"10381","relation_version_is_last":true,"title":["DeSVig: Decentralized Swift Vigilance Against Adversarial Attacks in Industrial Artificial Intelligence Systems"],"weko_creator_id":"18","weko_shared_id":-1},"updated":"2023-10-24T01:52:47.659155+00:00"}