Date of Award
Master of Science
Mark E. Dean, Audris Mockus
Monitoring systems are paramount to the proactive detection and mitigation of problems in computer networks related to performance and security. Degraded performance and compromised end-nodes can cost computer networks downtime, data loss and reputation. InSight2 is a platform that models, analyzes and visualizes large scale Argus network flow data using up-to-date geographical data, organizational information, and emerging threats. It is engineered to meet the needs of network administrators with flexibility and modularity in mind. Scalability is ensured by devising multi-core processing by implementing robust software architecture. Extendibility is achieved by enabling the end user to enrich flow records using additional user provided databases. Deployment is streamlined by providing an automated installation script. State-of-the-art visualizations are devised and presented in a secure, user friendly web interface giving greater insight about the network to the end user.
Kodituwakku, Hansaka Angel Dias Edirisinghe, "InSight2: An Interactive Web Based Platform for Modeling and Analysis of Large Scale Argus Network Flow Data. " Master's Thesis, University of Tennessee, 2017.