mlsanityData to 14 Oct 2026

Towards an Improved Understanding of Software Vulnerability Assessment Using Data-Driven Approaches

arXiv 2207.11708 ↗First posted 24 Jul 2022cs.SE cs.CR cs.LGcited by 1

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Abstract (arXiv)

The thesis advances the field of software security by providing knowledge and automation support for software vulnerability assessment using data-driven approaches. Software vulnerability assessment provides important and multifaceted information to prevent and mitigate dangerous cyber-attacks in the wild. The key contributions include a systematisation of knowledge, along with a suite of novel data-driven techniques and practical recommendations for researchers and practitioners in the area. The thesis results help improve the understanding and inform the practice of assessing ever-increasing vulnerabilities in real-world software systems. This in turn enables more thorough and timely fixing prioritisation and planning of these critical security issues.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 24 Jul 2022.

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