Towards an Improved Understanding of Software Vulnerability Assessment Using Data-Driven Approaches
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.
- Publication:
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arXiv e-prints
- Pub Date:
- July 2022
- DOI:
- 10.48550/arXiv.2207.11708
- arXiv:
- arXiv:2207.11708
- Bibcode:
- 2022arXiv220711708L
- Keywords:
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- Computer Science - Software Engineering;
- Computer Science - Cryptography and Security;
- Computer Science - Machine Learning
- E-Print:
- 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