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| 講演名 | 2024-10-26 14:45 CVE-Learn: Cybersecurity Study throughout the CVE Datasets for Learning Model-Based Processing ○Chidchanok Choksuchat・Sorawit Khumnaewnak・Touchai Angchuan・Nattawut Wichit・Sinchai Kamolphiwong（PSU）  IA2024-29 |
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| 抄録 | （和） | In our previous study, we gathered a dataset of daily Common Vulnerabilities and Exposures (CVEs) by scanning over 4,000 university subdomains. Each record contains over 30,000 rows, potentially accumulating millions of records annually. We collect this data weekly, making scalable monthly analysis challenging due to the limitations of local workstations without High-Performance Computing Infrastructure (HPCI). This research aims to test CVE analysis on HPCI, utilizing parallel processing in machine learning. Specifically, we compare accuracy and loss, along with validation of accuracy and loss, in deep neural networks (DNN) through the stages of model training and validation. |
| （英） | In our previous study, we gathered a dataset of daily Common Vulnerabilities and Exposures (CVEs) by scanning over 4,000 university subdomains. Each record contains over 30,000 rows, potentially accumulating millions of records annually. We collect this data weekly, making scalable monthly analysis challenging due to the limitations of local workstations without High-Performance Computing Infrastructure (HPCI). This research aims to test CVE analysis on HPCI, utilizing parallel processing in machine learning. Specifically, we compare accuracy and loss, along with validation of accuracy and loss, in deep neural networks (DNN) through the stages of model training and validation. | |
| キーワード | （和） | CVE (Common Vulnerabilities and Exposures) / Cybersecurity / High-Performance Computing Infrastructure (HPCI) / Parallel Processing / Machine Learning / Neural Networks / / |
| （英） | CVE (Common Vulnerabilities and Exposures) / Cybersecurity / High-Performance Computing Infrastructure (HPCI) / Parallel Processing / Machine Learning / Neural Networks / / | |
| 文献情報 | 信学技報, vol. 124, no. 225, IA2024-29, pp. 8-11, 2024年10月. | |
| 資料番号 | IA2024-29 | |
| 発行日 | 2024-10-19 (IA) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| 著作権に ついて |
技術研究報告に掲載された論文の著作権は電子情報通信学会に帰属します．(許諾番号：10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| PDFダウンロード | IA2024-29 |
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