A large literature exists that investigates the use of learning models for vulnerabilities detection. Even if it is well-recognized that the presence of code weaknesses (CWEs) in code fragments can make them vulnerable, most of the effort has been spent to propose new models and methods for the early detection of vulnerable code in a dataset of code fragments. This paper reports a preliminary study conducted to adopt Knowledge Graphs (KGs) for detecting the presence of CWEs in the code. The proposed approach has been evaluated on two datasets and has shown interesting results.

Towards a Knowledge Graph Based Approach for Vulnerable Code Weaknesses Identification / Vecellio Reane, Martina; Dall'Anese, Daniele; Lekeufack Foulefack, Rosmael Zidane; Marchetto, Alessandro. - (2025), pp. 159-166. (Intervento presentato al convegno 36th IFIP WG 6.1 International Conference on Testing Software and Systems (ICTSS 2024) tenutosi a London nel October 30 - November 1, 2024) [10.1007/978-3-031-80889-0_11].

Towards a Knowledge Graph Based Approach for Vulnerable Code Weaknesses Identification

Marchetto, Alessandro
2025-01-01

Abstract

A large literature exists that investigates the use of learning models for vulnerabilities detection. Even if it is well-recognized that the presence of code weaknesses (CWEs) in code fragments can make them vulnerable, most of the effort has been spent to propose new models and methods for the early detection of vulnerable code in a dataset of code fragments. This paper reports a preliminary study conducted to adopt Knowledge Graphs (KGs) for detecting the presence of CWEs in the code. The proposed approach has been evaluated on two datasets and has shown interesting results.
2025
Testing Software and Systems
Cham (SW)
Springer Cham
9783031808883
9783031808890
Vecellio Reane, Martina; Dall'Anese, Daniele; Lekeufack Foulefack, Rosmael Zidane; Marchetto, Alessandro
Towards a Knowledge Graph Based Approach for Vulnerable Code Weaknesses Identification / Vecellio Reane, Martina; Dall'Anese, Daniele; Lekeufack Foulefack, Rosmael Zidane; Marchetto, Alessandro. - (2025), pp. 159-166. (Intervento presentato al convegno 36th IFIP WG 6.1 International Conference on Testing Software and Systems (ICTSS 2024) tenutosi a London nel October 30 - November 1, 2024) [10.1007/978-3-031-80889-0_11].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/445811
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