Common Vulnerability Scoring System Prediction Based on Open Source Intelligence Information Sources [Data Set & Models]
| dc.contributor.author | Kuehn, Philipp | |
| dc.contributor.author | Relke, David | |
| dc.contributor.author | Reuter, Christian | |
| dc.date.accessioned | 2024-04-23T15:29:29Z | |
| dc.date.available | 2024-04-23T15:29:29Z | |
| dc.date.issued | 2023 | |
| dc.identifier.uri | https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/4214 | |
| dc.description | This repository contains the dataset used to train BERT-based models based on open information sources. We aimed to build a more robust model to predict the Common Vulnerability Scoring System (CVSS) score. The repository with the source code used to train and evaluate the models can be found in [this repository](https://github.com/PEASEC/Open-Information-CVSS-Prediction). Please cite the original paper when using this data: "Kuehn, P., Relke, D. N., & Reuter, C. (2023). Common vulnerability scoring system prediction based on open source intelligence information sources. Computers & Security" | de_DE |
| dc.relation | <p>is supplement to: <a href="https://doi.org/10.1016/j.cose.2023.103286">https://doi.org/10.1016/j.cose.2023.103286</a></p> | |
| dc.rights | MIT License | |
| dc.rights.uri | https://opensource.org/licenses/MIT | |
| dc.subject | Common vulnerability scoring system | de_DE |
| dc.subject | National vulnerability database | de_DE |
| dc.subject | Security management | de_DE |
| dc.subject | IT Security | de_DE |
| dc.subject | Deep learning | de_DE |
| dc.subject.classification | 409-05 Interaktive und intelligente Systeme, Bild- und Sprachverarbeitung, Computergraphik und Visualisierung | de_DE |
| dc.subject.ddc | 004 | |
| dc.title | Common Vulnerability Scoring System Prediction Based on Open Source Intelligence Information Sources [Data Set & Models] | de_DE |
| dc.type | Other | de_DE |
| tud.unit | TUDa |
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