{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00192273","sets":["6164:6165:6462:9599"]},"path":["9599"],"owner":"44499","recid":"192273","title":["API呼び出しとそれに伴う経過時間とシステム負荷を用いた重み付けスコアに基づくマルウェア検知手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2018-10-15"},"_buckets":{"deposit":"f892f369-990e-43a6-84e5-9229c83f1d09"},"_deposit":{"id":"192273","pid":{"type":"depid","value":"192273","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"API呼び出しとそれに伴う経過時間とシステム負荷を用いた重み付けスコアに基づくマルウェア検知手法","author_link":["447654","447659","447652","447647","447653","447650","447655","447657","447660","447649","447648","447646","447656","447651","447661","447658"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"API呼び出しとそれに伴う経過時間とシステム負荷を用いた重み付けスコアに基づくマルウェア検知手法"},{"subitem_title":"Malware Detection Method Using a Weighted Sum Model Based on API Call Patterns, Elapsed Time and System Load between API Calls","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"マルウェア検知，API，システム負荷，機械学習","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2018-10-15","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京情報大学総合情報学研究科"},{"subitem_text_value":"東京情報大学総合情報学部"},{"subitem_text_value":"筑波大学大学院システム情報工学研究科"},{"subitem_text_value":"東京情報大学総合情報学部"},{"subitem_text_value":"東京情報大学総合情報学部"},{"subitem_text_value":"東京情報大学総合情報学部"},{"subitem_text_value":"株式会社日立システムズサイバーセキュリティリサーチセンタ"},{"subitem_text_value":"株式会社日立システムズサイバーセキュリティリサーチセンタ"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Informatics, Tokyo University of Information Sciences","subitem_text_language":"en"},{"subitem_text_value":"Department of Information Sciences, Tokyo University of Information Sciences","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Systems and Information Engineering, University of Tsukuba","subitem_text_language":"en"},{"subitem_text_value":"Department of Information Sciences, Tokyo University of Information Sciences","subitem_text_language":"en"},{"subitem_text_value":"Department of Information Sciences, Tokyo University of Information Sciences","subitem_text_language":"en"},{"subitem_text_value":"Department of Information Sciences, Tokyo University of Information Sciences","subitem_text_language":"en"},{"subitem_text_value":"Hitachi Systems, Ltd. Cyber Security Research Center","subitem_text_language":"en"},{"subitem_text_value":"Hitachi Systems, Ltd. Cyber Security Research Center","subitem_text_language":"en"}]},"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/192273/files/IPSJCSS2018178.pdf","label":"IPSJCSS2018178.pdf"},"date":[{"dateType":"Available","dateValue":"2020-10-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJCSS2018178.pdf","filesize":[{"value":"645.4 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":"30"},{"tax":["include_tax"],"price":"0","billingrole":"46"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"d01a416e-acc8-4f39-afa7-0265807df9b9","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2018 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"佐藤, 順子"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"花田, 真樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"面, 和成"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"村上, 洋一"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鈴木, 英男"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"布広, 永示"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"折田, 彰"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"関口, 竜也"}],"nameIdentifiers":[{}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Junko, Sato","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Masaki, Hanada","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kazumasa, Omote","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yoichi, Murakami","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hideo, Suzuki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Eiji, Nunohiro","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Akira, Orita","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tatsuya, Sekiguchi","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_18_relation_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_select":"NCID","subitem_relation_type_id_text":"ISSN　1882-0840"}}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年, マルウェアの自身の隠蔽が巧妙化しており，未知のマルウェアを高精度で検知する手法が求められている．マルウェアは実行環境の検知，セキュリティサービスの無効化，自分自身の削除などの機能を用いて検知を免れようとしている. そこで筆者らはこれまで，API 呼び出しのパターンや経過時間, またシステム負荷の変動に関する特徴情報を用いた単純ベイズ分類器による検知手法を提案した.本研究では, 当該手法のさらなる検知精度向上のために，特徴情報ごとに分類器を作成し, それから算出されたスコアに重み付けをして足し合わせた値によってマルウェアを検知する手法の提案し，評価を行う.","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Malware detection method with high accuracy is strongly required, because mechanism of malware is getting sophisticated to evade detections by antivirus software. The cunning malware tries to evade detection using functions which detect the system environment, disable the security protection and remove myself. We have so far proposed a malware detection method based on API call pattern, elapsed time and system load between API calls. In this study, in order to make further improvement of the detection accuracy, we propose and evaluate a method using a weighted sum of scores from different classifiers constructed based on those features.","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"1270","bibliographic_titles":[{"bibliographic_title":"コンピュータセキュリティシンポジウム2018論文集"}],"bibliographicPageStart":"1266","bibliographicIssueNumber":"2","bibliographicVolumeNumber":"2018"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":192273,"updated":"2025-01-20T00:13:17.869441+00:00","links":{},"created":"2025-01-19T00:58:01.344951+00:00"}