| dc.contributor.advisor | Kepner, Jeremy | |
| dc.contributor.author | Lockton, Sophia E. | |
| dc.date.accessioned | 2025-10-06T17:36:16Z | |
| dc.date.available | 2025-10-06T17:36:16Z | |
| dc.date.issued | 2025-05 | |
| dc.date.submitted | 2025-06-23T14:02:54.859Z | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/162947 | |
| dc.description.abstract | Collaborative cyber defense is an essential strategy for detecting and mitigating cyber threats [1]. As traditional intrusion detection systems struggle against increasingly sophisticated attacks, we propose embedding collaborative cyber defense directly into system infrastructure. This work presents a novel implementation of collaborative awareness within DBOS (a Database-Oriented Operating System), resulting in a platform that significantly accelerates application development while providing built-in security for transactional web services. By treating security as a first-class operating system service, our approach facilitates real-time comprehensive network observation and analysis without the need for external tools. The implementation supports the construction, aggregation, and analysis of traffic matrices using both Python and PostgreSQL-based workflows. These workflows extract and process IP-level metadata from DBOS applications, enabling multi-instance aggregation and analysis of network data. This integration represents the first instance of collaborative network analysis within an operating system runtime, demonstrating that secure-by-default infrastructure is both feasible and performant. | |
| dc.publisher | Massachusetts Institute of Technology | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) | |
| dc.rights | Copyright retained by author(s) | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.title | DBOS Advanced Network Analysis Capability for Collaborative Awareness | |
| dc.type | Thesis | |
| dc.description.degree | M.Eng. | |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
| mit.thesis.degree | Master | |
| thesis.degree.name | Master of Engineering in Electrical Engineering and Computer Science | |