A model for automation of vulnerability summary generation by information identification, extraction, and aggregation from multiple sources

• Item type: Symposium(1)
• 公開日: 2023-10-23
• タイトル: A model for automation of vulnerability summary generation by information identification, extraction, and aggregation from multiple sources
• タイトル / 言語: en
• タイトル: A model for automation of vulnerability summary generation by information identification, extraction, and aggregation from multiple sources
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: Vulnerability management, automation, information aggregation, auto-summarization, NLP
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_5794
• 資源タイプ: conference paper
• 著者所属: Hitachi Ltd
• 著者所属: Hitachi Ltd
• 著者所属: Hitachi Ltd
• 著者所属: Hitachi Ltd
• 著者所属(英): en
• 著者所属(英): Hitachi Ltd
• 著者所属(英): en
• 著者所属(英): Hitachi Ltd
• 著者所属(英): en
• 著者所属(英): Hitachi Ltd
• 著者所属(英): en
• 著者所属(英): Hitachi Ltd
• 著者名: Ashokkumar, Chettymani; Nobuyoshi, Morita; Momoka, Kasuya; Hiroki, Yamazaki
• 著者名(英): Ashokkumar, Chettymani; Nobuyoshi, Morita; Momoka, Kasuya; Hiroki, Yamazaki
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Defending the IT/OT assets of an organization from cyber-attacks and addressing the vulnerability is a critical operation for Incident Response Team. To achieve it, the team has to collect, process, and understand various key aspects like attack type, patch, affected products, etc., from various trusted resources. This process is a time-consuming process and heavily relies on the skill sets of the security analyst. To address this challenge, we propose an automated model for identifying, extracting, and aggregating crucial cybersecurity information into a one-page summary. The model utilizes cybersecurity keywords to identify and extract the information from multiple sources, then combine them to generate a single page summary using NLP.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Defending the IT/OT assets of an organization from cyber-attacks and addressing the vulnerability is a critical operation for Incident Response Team. To achieve it, the team has to collect, process, and understand various key aspects like attack type, patch, affected products, etc., from various trusted resources. This process is a time-consuming process and heavily relies on the skill sets of the security analyst. To address this challenge, we propose an automated model for identifying, extracting, and aggregating crucial cybersecurity information into a one-page summary. The model utilizes cybersecurity keywords to identify and extract the information from multiple sources, then combine them to generate a single page summary using NLP.
• 書誌情報: コンピュータセキュリティシンポジウム2023論文集; p. 834-840, 発行日 2023-10-23
• 出版者 / 言語: ja
• 出版者: 情報処理学会