{"created":"2025-01-19T01:11:35.625057+00:00","updated":"2025-01-19T18:11:14.335932+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00210366","sets":["581:10433:10436"]},"path":["10436"],"owner":"44499","recid":"210366","title":["Novel Bi-directional Flow-based Traffic Generation Framework for IDS Evaluation and Exploratory Data Analysis"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-03-15"},"_buckets":{"deposit":"30635a20-c540-4fc0-816b-82091656aed9"},"_deposit":{"id":"210366","pid":{"type":"depid","value":"210366","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Novel Bi-directional Flow-based Traffic Generation Framework for IDS Evaluation and Exploratory Data Analysis","author_link":["532433","532434","532435","532432"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Novel Bi-directional Flow-based Traffic Generation Framework for IDS Evaluation and Exploratory Data Analysis"},{"subitem_title":"Novel Bi-directional Flow-based Traffic Generation Framework for IDS Evaluation and Exploratory Data Analysis","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"[一般論文] traffic modeling, protocol behavior model, traffic generation, network intrusion detection","subitem_subject_scheme":"Other"}]},"item_type_id":"2","publish_date":"2021-03-15","item_2_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Faculty of Information and Communication Technology, Mahidol University"},{"subitem_text_value":"Faculty of Information and Communication Technology, Mahidol University"}]},"item_2_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Faculty of Information and Communication Technology, Mahidol University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Information and Communication Technology, Mahidol University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"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/210366/files/IPSJ-JNL6203023.pdf","label":"IPSJ-JNL6203023.pdf"},"date":[{"dateType":"Available","dateValue":"2023-03-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-JNL6203023.pdf","filesize":[{"value":"775.4 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"5"},{"tax":["include_tax"],"price":"0","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"8"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"39af4e35-5af9-43f6-8368-50ef3e43e513","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_2_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Korakoch, Wilailux"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Sudsanguan, Ngamsuriyaroj"}],"nameIdentifiers":[{}]}]},"item_2_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Korakoch, Wilailux","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Sudsanguan, Ngamsuriyaroj","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_2_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00116647","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_2_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7764","subitem_source_identifier_type":"ISSN"}]},"item_2_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Flow-based network traffic information has been recently used to detect malicious intrusion. However, several available public flow-based datasets are unidirectional, and bidirectional flow-based datasets are rarely available. In this paper, a novel framework to generate bidirectional flow-based datasets for IDS evaluation is proposed. The generated dataset has the mixed combination of normal background traffic and attack traffic. The background traffic is based on the key traffic feature of the MAWI network traffic traces, and five popular attack traffics are generated based on their statistical traffic features. The generated dataset is characterized using the PCA approach, and we found out that benign and malicious traffic are distinct. With the proposed framework, a dataset of bi-directional flow-based traffic is generated and it would be used for evaluating an effective intrusion detection engine.\n------------------------------\nThis is a preprint of an article intended for publication Journal of\nInformation Processing(JIP). This preprint should not be cited. This\narticle should be cited as: Journal of Information Processing Vol.29(2021) (online)\nDOI http://dx.doi.org/10.2197/ipsjjip.29.256\n------------------------------","subitem_description_type":"Other"}]},"item_2_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Flow-based network traffic information has been recently used to detect malicious intrusion. However, several available public flow-based datasets are unidirectional, and bidirectional flow-based datasets are rarely available. In this paper, a novel framework to generate bidirectional flow-based datasets for IDS evaluation is proposed. The generated dataset has the mixed combination of normal background traffic and attack traffic. The background traffic is based on the key traffic feature of the MAWI network traffic traces, and five popular attack traffics are generated based on their statistical traffic features. The generated dataset is characterized using the PCA approach, and we found out that benign and malicious traffic are distinct. With the proposed framework, a dataset of bi-directional flow-based traffic is generated and it would be used for evaluating an effective intrusion detection engine.\n------------------------------\nThis is a preprint of an article intended for publication Journal of\nInformation Processing(JIP). This preprint should not be cited. This\narticle should be cited as: Journal of Information Processing Vol.29(2021) (online)\nDOI http://dx.doi.org/10.2197/ipsjjip.29.256\n------------------------------","subitem_description_type":"Other"}]},"item_2_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌"}],"bibliographicIssueDates":{"bibliographicIssueDate":"2021-03-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"3","bibliographicVolumeNumber":"62"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":210366,"links":{}}