@inproceedings{oai:ipsj.ixsq.nii.ac.jp:00228727,
 author = {Ashokkumar, Chettymani and Nobuyoshi, Morita and Momoka, Kasuya and Hiroki, Yamazaki and Ashokkumar, Chettymani and Nobuyoshi, Morita and Momoka, Kasuya and Hiroki, Yamazaki},
 book = {コンピュータセキュリティシンポジウム2023論文集},
 month = {Oct},
 note = {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., 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.},
 pages = {834--840},
 publisher = {情報処理学会},
 title = {A model for automation of vulnerability summary generation by information identification, extraction, and aggregation from multiple sources},
 year = {2023}
}