Process Mining Usage in Cybersecurity and Software Reliability Analysis: A Systematic Literature Review
| Authors | |
|---|---|
| Year of publication | 2022 |
| Type | Article in Periodical |
| Magazine / Source | Array |
| MU Faculty or unit | |
| Citation | |
| Web | https://www.sciencedirect.com/science/article/pii/S2590005621000576 |
| Doi | http://dx.doi.org/10.1016/j.array.2021.100120 |
| Keywords | Process mining; Cybersecurity; Software reliability; Systematic literature review |
| Description | The digitalization of our society is only possible in the presence of secure and reliable software systems governing ongoing critical processes, so-called critical information infrastructures. The understanding of mutual interdependencies of events and processes is crucial for cybersecurity and software reliability. One of the promising ways to tackle these challenges is process mining, which is a set of techniques that aims to mine essential knowledge from processes, thus providing more perspectives and temporal context to data interpretation and process understanding. However, it is unclear how process mining can help and can be practically used in the context of cybersecurity and reliability. Therefore, in this work, we investigate the potential of process mining to aid in cybersecurity and software reliability to analyze and support research efforts in these areas. Concretely, we collect existing process mining applications, discuss current trends and promising research directions that can be used to tackle the current cybersecurity and software reliability challenges. To this end, we conduct a systematic literature review covering 35 relevant research approaches to examine how the process mining is currently used for these tasks and what are the research gaps and promising research directions in the area. This work is an extension of our previous work, which focused solely on the cybersecurity area, based on the observation of relative closeness and similar goals of those two fields, in which some approaches tend to overlap. |
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