{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00219770","sets":["6164:6165:6640:11008"]},"path":["11008"],"owner":"44499","recid":"219770","title":["標的型攻撃の時系列データにおける1時間ごとの特徴と攻撃検知機械学習モデルの有用性検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-07-06"},"_buckets":{"deposit":"56921517-b662-4dfc-9fe5-3888925c8f4c"},"_deposit":{"id":"219770","pid":{"type":"depid","value":"219770","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"標的型攻撃の時系列データにおける1時間ごとの特徴と攻撃検知機械学習モデルの有用性検討","author_link":["573550","573551"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"標的型攻撃の時系列データにおける1時間ごとの特徴と攻撃検知機械学習モデルの有用性検討"}]},"item_type_id":"18","publish_date":"2022-07-06","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":"東邦大学"},{"subitem_text_value":"東邦大学"}]},"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/219770/files/IPSJ-DICOMO2022196.pdf","label":"IPSJ-DICOMO2022196.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-06"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2022196.pdf","filesize":[{"value":"3.4 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"79dc32c7-6b82-4cf9-8e40-666c8f6f591a","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"阿部, 衛"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"金岡, 晃"}],"nameIdentifiers":[{}]}]},"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":"標的型攻撃や APT（Advanced Persistent Threat）に対する検知技術の研究は，機械学習の採用など様々なアプローチで行われている．それらの研究を評価する際に用いられるデータセットも多くの種類が存在する．本研究では Los Alamos National Laboratory のデータセットに注目し，そのデータ特性調査と機械学習モデルへの適用の有用性の検討を行った．\nデータ特性の調査では，基礎調査により日ごとや週ごとの特徴がデータ量の推移から判明したため，1時間ごとに分割した時系列データのデータごとの関係性をクラスタリングを行い評価した．そしてそれらのデータを機械学習に適用する際の有用性を議論した．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"1411","bibliographic_titles":[{"bibliographic_title":"マルチメディア，分散，協調とモバイルシンポジウム2022論文集"}],"bibliographicPageStart":"1407","bibliographicIssueDates":{"bibliographicIssueDate":"2022-07-06","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2022"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":219770,"updated":"2025-01-19T14:47:06.198593+00:00","links":{},"created":"2025-01-19T01:19:49.887635+00:00"}