{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/162947"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/162947","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"DBOS Advanced Network Analysis Capability for Collaborative Awareness","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.","abstract_html":"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. 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