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Common Vulnerability Scoring System
Abstract
Historically, vendors have used their own methods for scoring software vulnerabilities, usually without detailing their criteria or processes. This creates a major problem for users, particularly those who manage disparate IT systems and applications. The Common Vulnerability Scoring System (CVSS) is a public initiative designed to address this issue by presenting a framework for assessing and quantifying the impact of software vulnerabilities. Organizations currently generating CVSS scores include Cisco, US National Institute of Standards and Technology (through the US National Vulnerability Database; NVD), Qualys, Oracle, and Tenable Network Security. CVSS offers the following benefits: 1) standardized vulnerability scores, 2) contextual scoring and 3) open framework. The goal is for CVSS to facilitate the generation of consistent scores that accurately represent the impact of vulnerabilities
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Cited by
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Cybersecurity of industrial cyber-physical systems: A review
Kayan, H., Nunes, M., Rana, O., Burnap, P., & Perera, C. (2022) · ACM Computing Surveys · doi:10.1145/3510410 · Cited by 261
Power system reliability evaluation with SCADA cybersecurity considerations
Zhang, Y., Wang, L., Xiang, Y., & Ten, C.-W. (2015) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2015.2396994 · Cited by 239
Modeling Cyber-Physical Vulnerability of the Smart Grid With Incomplete Information
Srivastava, A., Morris, T., Ernster, T., Vellaithurai, C., Pan, S., & Adhikari, U. (2013) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2012.2232318 · Cited by 169
Cyberthreat Detection from Twitter using Deep Neural Networks
Dionisio, N., Alves, F., Ferreira, P. M., & Bessani, A. (2019) · 2019 International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2019.8852475 · Cited by 126
Metadata
- Authors
- Mell, P., Scarfone, K., & Romanosky, S.
- Venue
- IEEE Security and Privacy Magazine
- Published
- 2006-11
- Volume
- 4
- Issue
- 6
- Pages
- 85-89
- ISSN
- 1540-7993 (ISSN-L)
- OpenAlex
- W2077937403
- Cited by
- 680
- References
- 0
- FWCI
- 38.89
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
