{"id":240890,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00240890","sets":["6164:6165:6462:11854"]},"path":["11854"],"owner":"11","recid":"240890","title":["日本を標的とするフィッシングサイトの特徴分析と攻撃グループの識別"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2024-10-15"},"_buckets":{"deposit":"9c159a15-f84c-46c5-a54a-e36fb2315292"},"_deposit":{"id":"240890","pid":{"type":"depid","value":"240890","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"日本を標的とするフィッシングサイトの特徴分析と攻撃グループの識別","author_link":["661982","661983","661984","661985","661986","661987","661988","661989","661990","661991"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"日本を標的とするフィッシングサイトの特徴分析と攻撃グループの識別","subitem_title_language":"ja"},{"subitem_title":"Characteristic Analysis and Attack Group Identification of Phishing Sites Targeting Japan","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"フィッシング, YARA, グルーピング, アトリビューション","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2024-10-15","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":"トレンドマイクロ株式会社／日本サイバー犯罪対策センター"},{"subitem_text_value":"トレンドマイクロ株式会社"},{"subitem_text_value":"千葉県警察本部 生活安全部 サイバー犯罪対策課／香川大学 創造工学部 電子・情報工学領域"},{"subitem_text_value":"神奈川県警察本部 サイバーセキュリティ対策本部／香川大学 創造工学部 電子・情報工学領域"},{"subitem_text_value":"香川大学 創造工学部 電子・情報工学領域"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Trend Micro, Inc. / Japan Cybercrime Control Center","subitem_text_language":"en"},{"subitem_text_value":"Trend Micro, Inc.","subitem_text_language":"en"},{"subitem_text_value":"Cybercrime Division, Community Safety Department, Chiba Prefectural Police Headquarters / Faculty of Engineering and Design, Kagawa University","subitem_text_language":"en"},{"subitem_text_value":"Cyber Security Task Force, Kanagawa Prefectural Police Headquarters / Faculty of Engineering and Design, Kagawa University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Engineering and Design, Kagawa University","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/240890/files/IPSJ-CSS2024144.pdf","label":"IPSJ-CSS2024144.pdf"},"date":[{"dateType":"Available","dateValue":"2026-10-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CSS2024144.pdf","filesize":[{"value":"468.8 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":"32c71242-8417-4cc2-9ea1-3c1321f8f6cd","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"松ヶ谷, 新吾"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"嶋村, 誠"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"竹重, 耕介"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"堺, 啓介"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"橋本, 正樹"}],"nameIdentifiers":[{}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shingo, Matsugaya","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Makoto, Shimamura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kousuke, Takeshige","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Keisuke, Sakai","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Masaki, Hashimoto","creatorNameLang":"en"}],"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":"近年，国内においてフィッシング被害が急増しており，2023年には件数・被害額共に過去最高であった．しかしながら，どのような攻撃主体によるフィッシングサイトが被害を多く発生させたかは明らかにはなっていない．本稿では国内を標的としたフィッシングサイトを分析し分類することで，攻撃主体を明らかにすることを試みた．分析対象は，JC3活動としてトレンドマイクロで運用する観測システムPhishHunterで2023年1月から2023年12月に収集したフィッシングサイトデータ255,929件を用いた．これらのデータを，フィッシングサイトのHTMLソースの特徴をYARAルール化したものを用いて，分類を行った．さらに，標的ブランドやIPアドレス，WHOIS情報等を収集して，HTMLソースの特徴と合わせて判断しグループ化した．結果，フィッシングサイトを213グループの分類に成功した．また，フィッシングサイトにおいてもHTMLソースによるグループ化が可能であることを示し，どのグループが最も活動的であったかを明らかにした．これにより，どの攻撃主体が被害を多く及ぼしているかの推論に貢献できる結果を創出できた．","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In recent years, phishing incidents have surged domestically, reaching an all-time high in both number and monetary losses in 2023. However, it remains unclear which attack entities are responsible for the most significant phishing damages. This paper attempts to identify these attack entities by analyzing and classifying phishing sites targeting Japanese users. The analysis utilized data from 255,929 phishing sites collected between January 2023 and December 2023 from PhishHunter, a phishing observation system operated by Trend Micro as a part of JC3 activities. Classification was performed using YARA rules based on characteristics of HTML source of phishing sites. Additionally, information such as target brands, IP addresses, and WHOIS data of phishing sites was collected and combined with the source characteristics to form groups. As a result, we successfully classified the phishing sites into 213 groups. This study demonstrates the feasibility of grouping phishing sites based on HTML source characteristics and identifies which groups were the most active. Consequently, the findings contribute to inferring which attack entities are causing the most significant harm. ","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"1079","bibliographic_titles":[{"bibliographic_title":"コンピュータセキュリティシンポジウム2024論文集"}],"bibliographicPageStart":"1072","bibliographicIssueDates":{"bibliographicIssueDate":"2024-10-15","bibliographicIssueDateType":"Issued"}}]},"relation_version_is_last":true,"weko_creator_id":"11"},"updated":"2025-03-06T05:55:29.467523+00:00","created":"2025-01-19T01:45:20.442823+00:00","links":{}}