Repositori institucional URV
| URV's Author/s: | Casino Cembellín, Francisco José |
| Author, as appears in the article.: | Guo Y; Bettaieb S; Casino F |
| Author's mail: | franciscojose.casino@urv.cat |
| Author identifier: | 0000-0003-4296-2876 |
| Journal publication year: | 2024 |
| Publication Type: | Journal Publications |
| APA: | Guo Y; Bettaieb S; Casino F (2024). A comprehensive analysis on software vulnerability detection datasets: trends, challenges, and road ahead. International Journal Of Information Security, 23(5), 3311-3327. DOI: 10.1007/s10207-024-00888-y |
| Paper original source: | International Journal Of Information Security. 23 (5): 3311-3327 |
| Abstract: | As society's dependence on information and communication systems (ICTs) grows, so does the necessity of guaranteeing the proper functioning and use of such systems. In this context, it is critical to enhance the security and robustness of the DevSecOps pipeline through timely vulnerability detection. Usually, AI-based models enable desirable features such as automation, performance, and efficacy. However, the quality of such models highly depends on the datasets used during the training stage. The latter encompasses a series of challenges yet to be solved, such as access to extensive labelled datasets with specific properties, such as well-represented and balanced samples. This article explores the current state of practice of software vulnerability datasets and provides a classification of the main challenges and issues. After an extensive analysis, it describes a set of guidelines and desirable features that datasets should guarantee. The latter is applied to create a new dataset, which fulfils these properties, along with a descriptive comparison with the state of the art. Finally, a discussion on how to foster good practices among researchers and practitioners sets the ground for further research and continued improvement within this critical domain. |
| Article's DOI: | 10.1007/s10207-024-00888-y |
| Link to the original source: | https://link.springer.com/article/10.1007/s10207-024-00888-y |
| Paper version: | info:eu-repo/semantics/publishedVersion |
| licence for use: | https://creativecommons.org/licenses/by/3.0/es/ |
| Department: | Enginyeria Informàtica i Matemàtiques |
| Licence document URL: | https://repositori.urv.cat/ca/proteccio-de-dades/ |
| Thematic Areas: | Ciência da computação Computer networks and communications Computer science, information systems Computer science, software engineering Computer science, theory & methods Engenharias iv Information systems Matemática / probabilidade e estatística Safety, risk, reliability and quality Software |
| Keywords: | Benchmarking Datasets Devsecop Devsecops Software vulnerability detection |
| Entity: | Universitat Rovira i Virgili |
| Record's date: | 2025-02-24 |
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