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機械学習を用いた Web アプリケーション攻撃検知手法の提案
http://hdl.handle.net/10098/10931
http://hdl.handle.net/10098/10931bf1b946b-4927-4b26-b85e-4c045899ea2f
名前 / ファイル | ライセンス | アクション |
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bd10122406.pdf (573.6 kB)
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Item type | 紀要論文 / Departmental Bulletin Paper(1) | |||||
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公開日 | 2020-04-01 | |||||
タイトル | ||||||
タイトル | 機械学習を用いた Web アプリケーション攻撃検知手法の提案 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Proposal of Web application attack detection method using machine learning | |||||
言語 | ||||||
言語 | jpn | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Security | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | HTTP Request | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Special Symbols | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Machine Learning | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | departmental bulletin paper | |||||
著者 |
清水, 大貴
× 清水, 大貴× 小高, 知宏× 黒岩, 丈介× 諏訪, いずみ× 白井, 治彦× Shimizu, Daiki× Odaka, Tomohiro× Kuroiwa, Jousuke× Suwa, Izumi× Shirai, Haruhiko |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | In this paper, we proposed two effective feature extraction methods for detecting intrusion in HTTP request sequences. We compared the classification accuracy of each proposed method using a machine learning. Attacks on Web applications are difficult to distinguish between normal and abnormal, and mechanical detection is not easy. Therefore, we focused on the fact that attacks on various Web applications are closely related to special symbols that differ from ordinary characters. As a result of classification using a method characterized by the number of occurrences of special symbols, the accuracy rate was about 95%. Also F-value and AUC are about 94% each. | |||||
書誌情報 |
福井大学 大学院工学研究科 研究報告 巻 68, p. 51-57, 発行日 2020-03 |
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出版者 | ||||||
出版者 | 福井大学 大学院工学研究科 | |||||
書誌レコードID | ||||||
識別子タイプ | NCID | |||||
関連識別子 | TD10122406 |