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Baswada, Thirupathi Reddy (2024) Enhancing Ransomware detection in Realtime using SIEM and IAM technologies in corporate networks. Masters thesis, Dublin, National College of Ireland.
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Abstract
By using a SIEM framework, that is enriched with existing knowledge of how Identity and Access are used over time in their organization. This project looks at improving ransomware detection within corporate networks. The project incorporates VirusTotal and YARA to be able operate as a full lifecycle monitoring solution, enabling it to identify ransomware threats in real time. Custom detection rules were written to identify ransomware-specific behaviors like file encryption, tampering with security software in order to proactively respond against newly discovered threats. Throughout the entire project, issues such as integration complexities and regular updates also surfaced to highlight the importance of continued maintenance work and resource allocation. Further work includes study of machine learning algorithms, detection methods and incident response improvements. This project has laid a stout foundation to evade the fearful ransomware threats amid corporate networks, saving vital assets.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Heffernan, Niall UNSPECIFIED |
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning |
| Divisions: | School of Computing > Master of Science in Cyber Security |
| Depositing User: | Ciara O'Brien |
| Date Deposited: | 29 Jul 2025 10:57 |
| Last Modified: | 29 Jul 2025 10:57 |
| URI: | https://norma.ncirl.ie/id/eprint/8296 |
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