Kyparos, Nikiforos (2023) Process Log Generation for Exploring Security Vulnerabilities and Violations in Business and Scientific Workflows. Bachelor's Thesis, Computing Science.
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Abstract
There is a growing need for security solutions to protect against anomalies that can occur in cloud-based business processes. Businesses are increasingly utilizing the cloud space for their data handling operations due to its scalable and flexible nature. Consequently, anomalies that range from inefficient procedures to malicious attacks have become ever more prevalent. Currently, businesses apply various methods to their processes to protect against abnormal behavior, including machine learning models that are trained on event log files and are capable of detecting anomalies. These files are extracted from the execution of the business process. However, based on our research, there is no comprehensive log file targeting the specific characteristics and requirements for detecting security and privacy violations. To address this gap, our focus is on exploring malicious attacks on the user's side of the process and generating event log files. In this research, we introduce a novel approach to generating log files for the user tasks of the business processes, aiming to enhance the robustness and accuracy of detection models.
| Item Type: | Thesis (Bachelor's Thesis) |
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| Supervisor name: | Karastoyanova, D. and Soveizi, N. |
| Degree programme: | Computing Science |
| Thesis type: | Bachelor's Thesis |
| Language: | English |
| Date Deposited: | 02 Aug 2023 11:31 |
| Last Modified: | 02 Aug 2023 11:31 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/31052 |
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