{"links":{},"id":194659,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00194659","sets":["1164:2836:9672:9716"]},"path":["9716"],"owner":"44499","recid":"194659","title":["画像特徴量による自己防衛機能を有したマルウェアの検知に関する検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-02-25"},"_buckets":{"deposit":"f03ae0c0-e90d-43da-bc30-b17fff917cbb"},"_deposit":{"id":"194659","pid":{"type":"depid","value":"194659","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"画像特徴量による自己防衛機能を有したマルウェアの検知に関する検討","author_link":["461368","461366","461367","461369","461370","461365"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"画像特徴量による自己防衛機能を有したマルウェアの検知に関する検討"},{"subitem_title":"A Study on Malware Detection with Self Defense Function by Image Features","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"マルウェア","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2019-02-25","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"日本大学"},{"subitem_text_value":"日本大学"},{"subitem_text_value":"日本大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Nihon University","subitem_text_language":"en"},{"subitem_text_value":"Nihon University","subitem_text_language":"en"},{"subitem_text_value":"Nihon 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/194659/files/IPSJ-DPS19178015.pdf","label":"IPSJ-DPS19178015.pdf"},"date":[{"dateType":"Available","dateValue":"2021-02-25"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DPS19178015.pdf","filesize":[{"value":"785.6 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"34"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"b8888078-8bdf-4e06-becf-7d2c45b1a199","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2019 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"小寺, 建輝"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"房安, 良和"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"泉, 隆"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Tateki, Kodera","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yoshikazu, Fusayasu","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takashi, Izumi","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10116224","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":"2188-8906","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，マルウェアの亜種生成が高速化され，パターンファイルの作成が追い付かない現状となっている．このような亜種検知に関する問題を解決するため，機械学習等により亜種を検知 ・ 分類する研究が多く取り組まれている．その中でも，機械語命令列等の静的解析情報をマルウェアの特徴とした研究では亜種を高い精度で検知 ・ 分類できることが確認されている．しかし，この手法はコンパイラの種類・最適化レベルの変更，ジャンクコードの挿入，パッキング等の機械語命令列に影響を与える自己防衛機能を有したマルウェア亜種の検知 ・ 分類に対しては精度が低下することが考えられる．本稿では，マルウェアのバイナリデータを画像として扱うことにより，機械語命令列のみに依存せず，上述の自己防衛機能を有したマルウェアの検知に有効な画像特徴量について検討を行った．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In recent years, the generation of subspecies has been accelerated, and the creation of the pattern file can not keep up with the present condition. In order to solve the problem related to such subspecies detection, many studies for detecting and classifying subspecies by machine learning are underway. Among them, it has been confirmed that subspecies can be detected and classified with high accuracy in studies that characterize static analysis information such as machine language instruction sequences as features of malware. However, this method is not suitable for detecting and classifying malware subspecies having a self-defense function that affects machine language instruction sequences such as change of compiler type / optimization level, junk code insertion, packing etc. It is thought that it will decrease. In this paper, we dealt with binary data of malware as an image, and examined image feature quantity effective for detection of malware having the above self - defense function, without relying solely on machine language instruction sequence.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告マルチメディア通信と分散処理（DPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2019-02-25","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"15","bibliographicVolumeNumber":"2019-DPS-178"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T00:59:41.922094+00:00","updated":"2025-01-19T23:23:57.944813+00:00"}