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

Software Engineering 2023-06-21 v3 Cryptography and Security Machine Learning

Abstract

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.

Keywords

Cite

@article{arxiv.2207.11708,
  title  = {Towards an Improved Understanding of Software Vulnerability Assessment Using Data-Driven Approaches},
  author = {Triet H. M. Le},
  journal= {arXiv preprint arXiv:2207.11708},
  year   = {2023}
}

Comments

A thesis submitted for the degree of Doctor of Philosophy at The University of Adelaide. The official version of the thesis can be found at the institutional repository: https://hdl.handle.net/2440/135914

R2 v1 2026-06-25T01:10:46.671Z